In [1]:

    

# load the package
include("../FractionalFlow/FractionalFlow.jl")
using PyPlot, SetPyPlot, Dierckx, Statistics, BlackBoxOptim
import Calculus
import GR
FF = FractionalFlow


    

    




┌ Info: Precompiling PyPlot [d330b81b-6aea-500a-939a-2ce795aea3ee]
└ @ Base loading.jl:1273
┌ Info: Precompiling Optim [429524aa-4258-5aef-a3af-852621145aeb]
└ @ Base loading.jl:1273
┌ Info: Precompiling SetPyPlot [d6c70c59-9b85-50b1-926c-19fb5cf24e7d]
└ @ Base loading.jl:1273
┌ Warning: Package SetPyPlot does not have PyPlot in its dependencies:
│ - If you have SetPyPlot checked out for development and have
│   added PyPlot as a dependency but haven't updated your primary
│   environment's manifest file, try `Pkg.resolve()`.
│ - Otherwise you may need to report an issue with SetPyPlot
└ Loading PyPlot into SetPyPlot from project dependency, future warnings for SetPyPlot are suppressed.






    
Out[1]:





Main.FractionalFlow

In [2]:

    

# define the problem
# relative permeabilities
rel_perms = FF.oil_water_rel_perms(krw0=0.4, kro0=0.9, 
    swc=0.15, sor=0.2, nw=2.0, no = 2.0)
# FF.visualize(rel_perms)
# define the fluids
fluids = FF.oil_water_fluids(mu_water=1e-3, mu_oil=1e-3)

# define the fractional flow functions
fw, dfw = FF.fractional_flow_function(rel_perms, fluids)
# visualize the fractional flow
# FF.visualize(rel_perms, fluids, label="lowsal")
# tight_layout()
ut = 1.15e-5
phi = 0.3
L = 0.15
core_flood = FF.core_flooding(u_inj=1.15e-5, pv_inject=5, 
    p_back=1e5, sw_init=0.2, sw_inj=1.0, rel_perms=rel_perms)
core_props = FF.core_properties()
wf_res = FF.water_flood(core_props, fluids, rel_perms, core_flood)
fw, dfw = FF.fractional_flow_function(rel_perms, fluids)
sw_tmp = FF.linspace(0,1,100)

FF.visualize(wf_res)


    

    













    













    













    













    













    
Out[2]:





PyObject <matplotlib.legend.Legend object at 0x0000000032B77B38>

In [3]:

    

t_sec, pv, rec_fact, dp_core, x, sw_face, c_face, c_out_sal=FF.water_flood_numeric(core_props, fluids, rel_perms, core_flood, Nx=50);


    

    




Progress: 100%|█████████████████████████████████████████| Time: 0:00:09

In [4]:

    

t_exp_dp = wf_res.dp_time[:,1]
dp_exp = wf_res.dp_time[:,2]
t_exp_R = wf_res.recovery_time[:,1]
R_exp = wf_res.recovery_time[:,2]
plotyy(t_exp_R, R_exp, t_exp_dp, dp_exp, fig_size = [8,5], x_label="time [s]", y1_label="R [-]", y2_label="dP [Pa]")


    

    













    
Out[4]:





(Figure(PyObject <Figure size 800x500 with 2 Axes>), PyObject <matplotlib.axes._subplots.AxesSubplot object at 0x0000000032D38898>, PyObject <matplotlib.axes._subplots.AxesSubplot object at 0x0000000032DFF278>)

In [5]:

    

plot(t_exp_dp, dp_exp, "o", t_sec, dp_core)
legend(["Analytical", "Numerical"])


    

    













    
Out[5]:





PyObject <matplotlib.legend.Legend object at 0x0000000031D666D8>

In [6]:

    

# struct
struct exp_data
    t_exp_dp
    dp_exp
    t_exp_R
    R_exp
end
exp_data1 = exp_data(t_exp_dp, dp_exp, t_exp_R, R_exp);


    

In [7]:

    

"""
rel_perm_param [krw0, kro0, nw, no, swc, sor]
"""
function error_calc(rel_perm_param, exp_data, core_props, fluids, core_flood; w_p=1.0, w_R=1.0)
    rel_perms = FF.oil_water_rel_perms(krw0=rel_perm_param[1], kro0=rel_perm_param[2], 
    swc=rel_perm_param[5], sor=rel_perm_param[6], nw=rel_perm_param[3], no = rel_perm_param[4])
    wf_res = FF.water_flood(core_props, fluids, rel_perms, core_flood)
    dp_calc = Spline1D(wf_res.dp_time[:,1], wf_res.dp_time[:,2], k=1, bc="nearest")
    R_calc = Spline1D(wf_res.recovery_time[:,1], wf_res.recovery_time[:,2], k=1, bc="nearest")
    error_dp = abs.(dp_calc(exp_data.t_exp_dp) .- exp_data.dp_exp)
#     println(error_dp)
    error_R = abs.(R_calc(exp_data.t_exp_R) .- exp_data.R_exp)
#     println(error_R)
    error_dp_norm = w_p.*error_dp./exp_data.dp_exp
    error_R_norm = w_R.*error_R./(exp_data.R_exp.+eps())
    return mean(error_R_norm)+mean(error_dp_norm)
end

function vis_error(rel_perm_param, exp_data, core_props, fluids, core_flood)
    rel_perms = FF.oil_water_rel_perms(krw0=rel_perm_param[1], kro0=rel_perm_param[2], 
    swc=rel_perm_param[5], sor=rel_perm_param[6], nw=rel_perm_param[3], no = rel_perm_param[4])
    wf_res = FF.water_flood(core_props, fluids, rel_perms, core_flood)
    figure()
    plot(wf_res.dp_time[:,1], wf_res.dp_time[:,2],  exp_data.t_exp_dp, exp_data.dp_exp, "o")
    xlabel("t [s]")
    ylabel("dp [Pa]")
    legend(["Theoretical", "Experiment"])
    
    figure()
    plot(wf_res.recovery_time[:,1], wf_res.recovery_time[:,2], exp_data.t_exp_R, exp_data.R_exp, "v")
    xlabel("t [s]")
    ylabel("R [-]")
    legend(["Theoretical", "Experiment"])
    
end

# test
x_init = [0.109681, 0.201297, 3.96653, 3.0, 0.19, 0.262231]

vis_error(x_init, exp_data1, core_props, fluids, core_flood)
error_calc(x_init, exp_data1, core_props, fluids, core_flood)


    

    













    













    
Out[7]:





4.57679065373876

In [8]:

    

# weight factors:
w_p = ones(length(exp_data1.dp_exp))
temp_val, ind_max = findmax(exp_data1.dp_exp)
println(ind_max)
w_p[ind_max-3:ind_max+3] .= 10
w_p[end-10:end] .= 10
w_p[1]=10
w_R = ones(length(exp_data1.R_exp))
w_R[20:25] .= 10
w_R[end-3:end] .= 10


function f(x)
    f_val = 0.0
    try
        f_val = error_calc(x, exp_data1, core_props, fluids, core_flood, w_p = w_p, w_R = w_R)
    catch
        f_val = 100.0
#         info("Objective function did not converge!")
    end
    return f_val
end

    
function g(x)
    eps1 = 1e-3
    f_val = f(x)
    g_val = ones(length(x))
    try
        # g_val = Calculus.gradient(x -> error_calc(x, exp_data1, core_props, fluids, core_flood), x)
        for j in eachindex(x)
            x2 = copy(x)
            x2[j]+=eps1
            f_val2 = f(x2)
            g_val[j] = (f_val2-f_val)/eps1
        end
    catch
        g_val = ones(length(x))
    end
    return g_val
end

function obj_fun(param, grad)
    if length(grad)>0
      grad[:] = g(param)
    end
    
    obj_fun_val = f(param)
    if isnan(obj_fun_val) || isinf(obj_fun_val)
        obj_fun_val = 100.0
    end
    return obj_fun_val
end

# test
grad_x = zeros(6)
obj_fun([1.0, 0.8, 3, 4, 0.2, 0.2], grad_x)

f([1.0, 0.8, 2, 2, 0.1, 0.2])


    

    




23






    
Out[8]:





1.0713534659832842

In [9]:

    

grad_x


    

    
Out[9]:





6-element Array{Float64,1}:
  0.559755747851276   
  0.007055679254075464
 -0.23785704697598664 
 -0.04586750588075894 
 -0.8425478566016498  
  1.8982879302710254  

In [10]:

    

x_init = [0.9, 0.8, 2.5, 2.5, 0.1, 0.1]
x_lb = [0.1, 0.1, 1.5, 1.5, 0.05, 0.1]
x_ub = [1.0, 1.0, 4.0, 4.0, core_flood.initial_water_saturation, 0.25]

res = bboptimize(f, SearchRange = [(0.1, 1.0), (0.1, 1.0), (1.5, 4.0), (1.5, 4.0), 
        (0.05, core_flood.initial_water_saturation), (0.1, 0.25)])
 
#    NumDimensions = 6, Method = :de_rand_1_bin)

# opt_alg=:LD_SLSQP
# opt1 = Opt(opt_alg, length(x_init)) # choose the algorithm
# lower_bounds!(opt1, x_lb)
# upper_bounds!(opt1, x_ub)
# ftol_rel!(opt1, 1e-15)
# ftol_abs!(opt1, 1e-15)

# min_objective!(opt1, obj_fun)
# (fObjOpt, paramOpt, flag) = optimize(opt1, x_init)


    

    




Starting optimization with optimizer DiffEvoOpt{FitPopulation{Float64},RadiusLimitedSelector,BlackBoxOptim.AdaptiveDiffEvoRandBin{3},RandomBound{ContinuousRectSearchSpace}}
0.00 secs, 0 evals, 0 steps
0.58 secs, 10 evals, 5 steps, improv/step: 0.800 (last = 0.8000), fitness=0.611312982
1.14 secs, 21 evals, 11 steps, improv/step: 0.727 (last = 0.6667), fitness=0.529325847
1.66 secs, 33 evals, 18 steps, improv/step: 0.556 (last = 0.2857), fitness=0.415254671
2.19 secs, 44 evals, 24 steps, improv/step: 0.500 (last = 0.3333), fitness=0.282775545
2.71 secs, 56 evals, 31 steps, improv/step: 0.516 (last = 0.5714), fitness=0.282775545
3.25 secs, 68 evals, 37 steps, improv/step: 0.514 (last = 0.5000), fitness=0.179274381
3.77 secs, 80 evals, 44 steps, improv/step: 0.523 (last = 0.5714), fitness=0.179274381
4.32 secs, 92 evals, 52 steps, improv/step: 0.500 (last = 0.3750), fitness=0.179274381
4.84 secs, 104 evals, 59 steps, improv/step: 0.508 (last = 0.5714), fitness=0.179274381
5.38 secs, 116 evals, 68 steps, improv/step: 0.529 (last = 0.6667), fitness=0.179274381
5.90 secs, 127 evals, 76 steps, improv/step: 0.539 (last = 0.6250), fitness=0.096299767
6.55 secs, 139 evals, 84 steps, improv/step: 0.512 (last = 0.2500), fitness=0.096299767
7.10 secs, 151 evals, 92 steps, improv/step: 0.522 (last = 0.6250), fitness=0.096299767
7.67 secs, 164 evals, 101 steps, improv/step: 0.485 (last = 0.1111), fitness=0.096299767
8.24 secs, 177 evals, 110 steps, improv/step: 0.482 (last = 0.4444), fitness=0.096299767
8.77 secs, 189 evals, 120 steps, improv/step: 0.450 (last = 0.1000), fitness=0.096299767
9.30 secs, 200 evals, 130 steps, improv/step: 0.446 (last = 0.4000), fitness=0.096299767
9.85 secs, 212 evals, 139 steps, improv/step: 0.432 (last = 0.2222), fitness=0.096299767
10.42 secs, 224 evals, 149 steps, improv/step: 0.436 (last = 0.5000), fitness=0.096299767
10.94 secs, 236 evals, 159 steps, improv/step: 0.440 (last = 0.5000), fitness=0.096299767
11.50 secs, 248 evals, 169 steps, improv/step: 0.444 (last = 0.5000), fitness=0.096299767
12.04 secs, 260 evals, 181 steps, improv/step: 0.448 (last = 0.5000), fitness=0.096299767
12.61 secs, 271 evals, 191 steps, improv/step: 0.435 (last = 0.2000), fitness=0.096299767
13.14 secs, 281 evals, 200 steps, improv/step: 0.435 (last = 0.4444), fitness=0.096299767
13.65 secs, 292 evals, 210 steps, improv/step: 0.429 (last = 0.3000), fitness=0.096299767
14.19 secs, 303 evals, 220 steps, improv/step: 0.432 (last = 0.5000), fitness=0.096299767
14.71 secs, 314 evals, 231 steps, improv/step: 0.433 (last = 0.4545), fitness=0.096299767
15.26 secs, 324 evals, 239 steps, improv/step: 0.435 (last = 0.5000), fitness=0.096299767
16.00 secs, 328 evals, 241 steps, improv/step: 0.436 (last = 0.5000), fitness=0.096299767
16.53 secs, 336 evals, 249 steps, improv/step: 0.442 (last = 0.6250), fitness=0.096299767
17.04 secs, 347 evals, 260 steps, improv/step: 0.438 (last = 0.3636), fitness=0.096299767
17.55 secs, 359 evals, 271 steps, improv/step: 0.432 (last = 0.2727), fitness=0.096299767
18.09 secs, 371 evals, 283 steps, improv/step: 0.428 (last = 0.3333), fitness=0.096299767
18.60 secs, 383 evals, 295 steps, improv/step: 0.420 (last = 0.2500), fitness=0.096299767
19.14 secs, 395 evals, 307 steps, improv/step: 0.410 (last = 0.1667), fitness=0.096299767
19.66 secs, 407 evals, 318 steps, improv/step: 0.403 (last = 0.1818), fitness=0.096299767
20.16 secs, 418 evals, 329 steps, improv/step: 0.398 (last = 0.2727), fitness=0.096299767
20.68 secs, 430 evals, 341 steps, improv/step: 0.399 (last = 0.4167), fitness=0.096299767
21.18 secs, 441 evals, 352 steps, improv/step: 0.398 (last = 0.3636), fitness=0.096299767
21.71 secs, 453 evals, 364 steps, improv/step: 0.393 (last = 0.2500), fitness=0.096299767
22.22 secs, 464 evals, 375 steps, improv/step: 0.387 (last = 0.1818), fitness=0.096299767
22.73 secs, 471 evals, 382 steps, improv/step: 0.382 (last = 0.1429), fitness=0.096299767
23.23 secs, 478 evals, 389 steps, improv/step: 0.380 (last = 0.2857), fitness=0.096299767
23.74 secs, 489 evals, 400 steps, improv/step: 0.375 (last = 0.1818), fitness=0.096299767
24.27 secs, 501 evals, 412 steps, improv/step: 0.369 (last = 0.1667), fitness=0.096299767
24.77 secs, 512 evals, 423 steps, improv/step: 0.369 (last = 0.3636), fitness=0.096299767
25.30 secs, 524 evals, 435 steps, improv/step: 0.361 (last = 0.0833), fitness=0.096299767
25.85 secs, 535 evals, 446 steps, improv/step: 0.363 (last = 0.4545), fitness=0.096299767
26.38 secs, 546 evals, 457 steps, improv/step: 0.359 (last = 0.1818), fitness=0.096299767
26.90 secs, 558 evals, 469 steps, improv/step: 0.356 (last = 0.2500), fitness=0.091782119
27.44 secs, 570 evals, 481 steps, improv/step: 0.351 (last = 0.1667), fitness=0.091782119
27.96 secs, 581 evals, 492 steps, improv/step: 0.346 (last = 0.0909), fitness=0.091782119
28.46 secs, 592 evals, 503 steps, improv/step: 0.342 (last = 0.1818), fitness=0.091782119
28.99 secs, 604 evals, 515 steps, improv/step: 0.340 (last = 0.2500), fitness=0.091782119
29.53 secs, 616 evals, 527 steps, improv/step: 0.342 (last = 0.4167), fitness=0.082123283
30.07 secs, 628 evals, 539 steps, improv/step: 0.338 (last = 0.1667), fitness=0.082123283
30.60 secs, 640 evals, 551 steps, improv/step: 0.332 (last = 0.0833), fitness=0.082123283
31.13 secs, 652 evals, 563 steps, improv/step: 0.330 (last = 0.2500), fitness=0.082123283
31.66 secs, 664 evals, 575 steps, improv/step: 0.329 (last = 0.2500), fitness=0.082123283
32.18 secs, 676 evals, 587 steps, improv/step: 0.324 (last = 0.0833), fitness=0.082123283
32.68 secs, 687 evals, 598 steps, improv/step: 0.326 (last = 0.4545), fitness=0.082123283
33.22 secs, 699 evals, 610 steps, improv/step: 0.321 (last = 0.0833), fitness=0.082123283
33.76 secs, 711 evals, 622 steps, improv/step: 0.318 (last = 0.1667), fitness=0.082123283
34.27 secs, 723 evals, 634 steps, improv/step: 0.315 (last = 0.1667), fitness=0.082123283
34.82 secs, 730 evals, 641 steps, improv/step: 0.317 (last = 0.4286), fitness=0.081739619
35.34 secs, 742 evals, 653 steps, improv/step: 0.314 (last = 0.1667), fitness=0.081739619
35.87 secs, 753 evals, 664 steps, improv/step: 0.312 (last = 0.1818), fitness=0.081739619
36.41 secs, 762 evals, 673 steps, improv/step: 0.312 (last = 0.3333), fitness=0.081739619
36.96 secs, 772 evals, 683 steps, improv/step: 0.313 (last = 0.4000), fitness=0.081711681
37.50 secs, 782 evals, 693 steps, improv/step: 0.310 (last = 0.1000), fitness=0.081711681
38.04 secs, 794 evals, 705 steps, improv/step: 0.309 (last = 0.2500), fitness=0.081711681
38.55 secs, 805 evals, 716 steps, improv/step: 0.307 (last = 0.1818), fitness=0.081711681
39.08 secs, 817 evals, 728 steps, improv/step: 0.305 (last = 0.1667), fitness=0.081711681
39.62 secs, 829 evals, 740 steps, improv/step: 0.305 (last = 0.3333), fitness=0.042690271
40.14 secs, 841 evals, 752 steps, improv/step: 0.305 (last = 0.2500), fitness=0.042690271
40.68 secs, 853 evals, 764 steps, improv/step: 0.300 (last = 0.0000), fitness=0.042690271
41.21 secs, 865 evals, 776 steps, improv/step: 0.300 (last = 0.3333), fitness=0.042690271
41.73 secs, 877 evals, 788 steps, improv/step: 0.301 (last = 0.3333), fitness=0.042690271
42.25 secs, 889 evals, 800 steps, improv/step: 0.299 (last = 0.1667), fitness=0.042690271
42.80 secs, 899 evals, 810 steps, improv/step: 0.300 (last = 0.4000), fitness=0.042690271
43.33 secs, 911 evals, 822 steps, improv/step: 0.299 (last = 0.2500), fitness=0.042690271
43.85 secs, 923 evals, 834 steps, improv/step: 0.299 (last = 0.2500), fitness=0.042690271
44.36 secs, 931 evals, 842 steps, improv/step: 0.299 (last = 0.3750), fitness=0.042690271
44.88 secs, 943 evals, 854 steps, improv/step: 0.301 (last = 0.4167), fitness=0.042690271
45.40 secs, 955 evals, 866 steps, improv/step: 0.298 (last = 0.0833), fitness=0.042690271
45.90 secs, 966 evals, 877 steps, improv/step: 0.296 (last = 0.1818), fitness=0.042690271
46.42 secs, 977 evals, 888 steps, improv/step: 0.295 (last = 0.1818), fitness=0.042690271
46.95 secs, 989 evals, 900 steps, improv/step: 0.294 (last = 0.2500), fitness=0.041974691
47.48 secs, 1001 evals, 912 steps, improv/step: 0.294 (last = 0.2500), fitness=0.041974691
48.01 secs, 1013 evals, 924 steps, improv/step: 0.291 (last = 0.0833), fitness=0.041974691
48.55 secs, 1025 evals, 936 steps, improv/step: 0.290 (last = 0.1667), fitness=0.041974691
49.09 secs, 1037 evals, 948 steps, improv/step: 0.288 (last = 0.1667), fitness=0.041974691
49.61 secs, 1049 evals, 960 steps, improv/step: 0.284 (last = 0.0000), fitness=0.041974691
50.15 secs, 1061 evals, 972 steps, improv/step: 0.286 (last = 0.4167), fitness=0.041974691
50.66 secs, 1073 evals, 984 steps, improv/step: 0.286 (last = 0.2500), fitness=0.037742314
51.18 secs, 1085 evals, 996 steps, improv/step: 0.285 (last = 0.2500), fitness=0.037742314
51.70 secs, 1097 evals, 1008 steps, improv/step: 0.285 (last = 0.2500), fitness=0.037742314
52.22 secs, 1109 evals, 1020 steps, improv/step: 0.282 (last = 0.0833), fitness=0.037742314
52.73 secs, 1121 evals, 1032 steps, improv/step: 0.281 (last = 0.1667), fitness=0.037742314
53.27 secs, 1133 evals, 1044 steps, improv/step: 0.278 (last = 0.0000), fitness=0.037742314
53.80 secs, 1145 evals, 1056 steps, improv/step: 0.277 (last = 0.1667), fitness=0.037742314
54.33 secs, 1157 evals, 1068 steps, improv/step: 0.276 (last = 0.2500), fitness=0.037742314
54.84 secs, 1169 evals, 1080 steps, improv/step: 0.276 (last = 0.2500), fitness=0.037742314
55.38 secs, 1180 evals, 1091 steps, improv/step: 0.275 (last = 0.1818), fitness=0.037742314
55.90 secs, 1192 evals, 1103 steps, improv/step: 0.276 (last = 0.3333), fitness=0.037742314
56.44 secs, 1203 evals, 1114 steps, improv/step: 0.275 (last = 0.1818), fitness=0.037742314
56.96 secs, 1215 evals, 1126 steps, improv/step: 0.275 (last = 0.3333), fitness=0.037742314
57.50 secs, 1227 evals, 1138 steps, improv/step: 0.276 (last = 0.3333), fitness=0.037742314
58.02 secs, 1239 evals, 1150 steps, improv/step: 0.275 (last = 0.1667), fitness=0.037742314
58.55 secs, 1249 evals, 1160 steps, improv/step: 0.273 (last = 0.1000), fitness=0.037742314
59.07 secs, 1261 evals, 1172 steps, improv/step: 0.271 (last = 0.0833), fitness=0.037742314
59.60 secs, 1273 evals, 1184 steps, improv/step: 0.270 (last = 0.1667), fitness=0.037742314
60.13 secs, 1285 evals, 1196 steps, improv/step: 0.268 (last = 0.0833), fitness=0.037742314
60.65 secs, 1297 evals, 1208 steps, improv/step: 0.267 (last = 0.1667), fitness=0.037742314
61.17 secs, 1309 evals, 1220 steps, improv/step: 0.267 (last = 0.2500), fitness=0.037742314
61.73 secs, 1321 evals, 1232 steps, improv/step: 0.267 (last = 0.2500), fitness=0.037399579
62.25 secs, 1333 evals, 1244 steps, improv/step: 0.267 (last = 0.2500), fitness=0.037399579
62.76 secs, 1345 evals, 1256 steps, improv/step: 0.267 (last = 0.2500), fitness=0.037399579
63.27 secs, 1356 evals, 1267 steps, improv/step: 0.266 (last = 0.1818), fitness=0.035683268
63.82 secs, 1365 evals, 1276 steps, improv/step: 0.266 (last = 0.2222), fitness=0.035683268
64.35 secs, 1373 evals, 1284 steps, improv/step: 0.266 (last = 0.3750), fitness=0.035683268
64.86 secs, 1380 evals, 1291 steps, improv/step: 0.265 (last = 0.0000), fitness=0.035683268
65.36 secs, 1387 evals, 1298 steps, improv/step: 0.265 (last = 0.2857), fitness=0.035683268
65.89 secs, 1393 evals, 1304 steps, improv/step: 0.265 (last = 0.1667), fitness=0.035683268
66.41 secs, 1400 evals, 1311 steps, improv/step: 0.265 (last = 0.2857), fitness=0.035369366
66.91 secs, 1406 evals, 1317 steps, improv/step: 0.266 (last = 0.5000), fitness=0.035369366
67.49 secs, 1414 evals, 1325 steps, improv/step: 0.265 (last = 0.1250), fitness=0.035369366
68.01 secs, 1421 evals, 1332 steps, improv/step: 0.264 (last = 0.1429), fitness=0.035369366
68.52 secs, 1428 evals, 1339 steps, improv/step: 0.264 (last = 0.1429), fitness=0.035369366
69.08 secs, 1435 evals, 1346 steps, improv/step: 0.263 (last = 0.1429), fitness=0.035369366
69.61 secs, 1441 evals, 1352 steps, improv/step: 0.264 (last = 0.5000), fitness=0.035369366
70.17 secs, 1449 evals, 1360 steps, improv/step: 0.265 (last = 0.3750), fitness=0.035369366
70.70 secs, 1458 evals, 1369 steps, improv/step: 0.267 (last = 0.5556), fitness=0.035369366
71.22 secs, 1468 evals, 1379 steps, improv/step: 0.265 (last = 0.1000), fitness=0.035369366
71.75 secs, 1480 evals, 1391 steps, improv/step: 0.263 (last = 0.0000), fitness=0.035369366
72.29 secs, 1492 evals, 1403 steps, improv/step: 0.263 (last = 0.2500), fitness=0.024901854
72.84 secs, 1503 evals, 1414 steps, improv/step: 0.263 (last = 0.2727), fitness=0.024901854
73.34 secs, 1509 evals, 1420 steps, improv/step: 0.263 (last = 0.1667), fitness=0.024901854
73.91 secs, 1513 evals, 1424 steps, improv/step: 0.262 (last = 0.0000), fitness=0.024901854
74.42 secs, 1523 evals, 1434 steps, improv/step: 0.262 (last = 0.3000), fitness=0.024901854
75.04 secs, 1534 evals, 1445 steps, improv/step: 0.262 (last = 0.1818), fitness=0.024901854
75.58 secs, 1545 evals, 1456 steps, improv/step: 0.261 (last = 0.1818), fitness=0.024901854
76.11 secs, 1557 evals, 1468 steps, improv/step: 0.262 (last = 0.4167), fitness=0.024901854
76.64 secs, 1567 evals, 1478 steps, improv/step: 0.263 (last = 0.4000), fitness=0.024901854
77.17 secs, 1579 evals, 1490 steps, improv/step: 0.262 (last = 0.0833), fitness=0.024901854
77.72 secs, 1591 evals, 1502 steps, improv/step: 0.261 (last = 0.1667), fitness=0.024901854
78.23 secs, 1603 evals, 1514 steps, improv/step: 0.264 (last = 0.6667), fitness=0.024901854
78.76 secs, 1615 evals, 1526 steps, improv/step: 0.263 (last = 0.1667), fitness=0.024901854
79.28 secs, 1627 evals, 1538 steps, improv/step: 0.263 (last = 0.2500), fitness=0.024901854
79.79 secs, 1636 evals, 1547 steps, improv/step: 0.262 (last = 0.1111), fitness=0.024901854
80.32 secs, 1648 evals, 1559 steps, improv/step: 0.262 (last = 0.1667), fitness=0.024901854
80.87 secs, 1658 evals, 1569 steps, improv/step: 0.262 (last = 0.3000), fitness=0.024901854
81.39 secs, 1670 evals, 1581 steps, improv/step: 0.261 (last = 0.1667), fitness=0.024901854
81.92 secs, 1682 evals, 1593 steps, improv/step: 0.261 (last = 0.1667), fitness=0.024901854
82.44 secs, 1694 evals, 1605 steps, improv/step: 0.260 (last = 0.2500), fitness=0.024901854
82.97 secs, 1704 evals, 1615 steps, improv/step: 0.261 (last = 0.3000), fitness=0.024901854
83.54 secs, 1712 evals, 1623 steps, improv/step: 0.261 (last = 0.2500), fitness=0.024901854
84.05 secs, 1721 evals, 1632 steps, improv/step: 0.261 (last = 0.3333), fitness=0.024901854
84.56 secs, 1732 evals, 1643 steps, improv/step: 0.259 (last = 0.0000), fitness=0.024901854
85.06 secs, 1743 evals, 1654 steps, improv/step: 0.258 (last = 0.0000), fitness=0.024901854
85.59 secs, 1754 evals, 1665 steps, improv/step: 0.256 (last = 0.0909), fitness=0.024901854
86.12 secs, 1765 evals, 1676 steps, improv/step: 0.257 (last = 0.3636), fitness=0.024901854
86.66 secs, 1776 evals, 1687 steps, improv/step: 0.258 (last = 0.3636), fitness=0.018611812
87.17 secs, 1780 evals, 1691 steps, improv/step: 0.257 (last = 0.0000), fitness=0.018611812
87.71 secs, 1786 evals, 1697 steps, improv/step: 0.256 (last = 0.0000), fitness=0.018611812
88.24 secs, 1793 evals, 1704 steps, improv/step: 0.255 (last = 0.0000), fitness=0.018611812
88.74 secs, 1801 evals, 1712 steps, improv/step: 0.255 (last = 0.1250), fitness=0.018611812
89.33 secs, 1809 evals, 1720 steps, improv/step: 0.254 (last = 0.1250), fitness=0.018611812
89.88 secs, 1815 evals, 1726 steps, improv/step: 0.254 (last = 0.1667), fitness=0.018611812
90.42 secs, 1822 evals, 1733 steps, improv/step: 0.253 (last = 0.0000), fitness=0.018611812
90.97 secs, 1829 evals, 1740 steps, improv/step: 0.253 (last = 0.4286), fitness=0.018611812
91.65 secs, 1836 evals, 1747 steps, improv/step: 0.254 (last = 0.2857), fitness=0.018611812
92.19 secs, 1840 evals, 1751 steps, improv/step: 0.254 (last = 0.5000), fitness=0.018611812
92.72 secs, 1848 evals, 1759 steps, improv/step: 0.253 (last = 0.0000), fitness=0.018611812
93.23 secs, 1859 evals, 1770 steps, improv/step: 0.253 (last = 0.2727), fitness=0.018611812
93.75 secs, 1870 evals, 1781 steps, improv/step: 0.252 (last = 0.0000), fitness=0.018611812
94.29 secs, 1879 evals, 1790 steps, improv/step: 0.250 (last = 0.0000), fitness=0.018611812
94.80 secs, 1890 evals, 1801 steps, improv/step: 0.250 (last = 0.1818), fitness=0.018611812
95.32 secs, 1899 evals, 1810 steps, improv/step: 0.251 (last = 0.4444), fitness=0.018611812
95.83 secs, 1911 evals, 1822 steps, improv/step: 0.250 (last = 0.1667), fitness=0.018611812
96.37 secs, 1923 evals, 1834 steps, improv/step: 0.250 (last = 0.2500), fitness=0.018611812
96.87 secs, 1932 evals, 1843 steps, improv/step: 0.250 (last = 0.2222), fitness=0.018611812
97.40 secs, 1944 evals, 1855 steps, improv/step: 0.251 (last = 0.3333), fitness=0.018611812
97.91 secs, 1952 evals, 1863 steps, improv/step: 0.251 (last = 0.2500), fitness=0.018611812
98.56 secs, 1961 evals, 1872 steps, improv/step: 0.251 (last = 0.2222), fitness=0.018611812
99.07 secs, 1969 evals, 1880 steps, improv/step: 0.251 (last = 0.3750), fitness=0.018611812
99.58 secs, 1980 evals, 1891 steps, improv/step: 0.251 (last = 0.1818), fitness=0.018611812
100.11 secs, 1992 evals, 1903 steps, improv/step: 0.250 (last = 0.1667), fitness=0.018611812
100.62 secs, 2001 evals, 1912 steps, improv/step: 0.250 (last = 0.2222), fitness=0.018611812
101.14 secs, 2012 evals, 1923 steps, improv/step: 0.250 (last = 0.2727), fitness=0.018611812
101.67 secs, 2023 evals, 1934 steps, improv/step: 0.249 (last = 0.0000), fitness=0.018611812
102.19 secs, 2035 evals, 1946 steps, improv/step: 0.248 (last = 0.0833), fitness=0.018611812
102.70 secs, 2046 evals, 1957 steps, improv/step: 0.247 (last = 0.1818), fitness=0.018611812
103.23 secs, 2056 evals, 1967 steps, improv/step: 0.246 (last = 0.0000), fitness=0.018611812
103.86 secs, 2060 evals, 1971 steps, improv/step: 0.247 (last = 0.5000), fitness=0.018611812
104.38 secs, 2065 evals, 1976 steps, improv/step: 0.246 (last = 0.2000), fitness=0.018611812
104.94 secs, 2075 evals, 1986 steps, improv/step: 0.247 (last = 0.3000), fitness=0.018611812
105.46 secs, 2086 evals, 1997 steps, improv/step: 0.245 (last = 0.0000), fitness=0.018611812
105.98 secs, 2097 evals, 2008 steps, improv/step: 0.244 (last = 0.0000), fitness=0.018611812
106.50 secs, 2108 evals, 2019 steps, improv/step: 0.244 (last = 0.1818), fitness=0.018611812
107.00 secs, 2119 evals, 2030 steps, improv/step: 0.242 (last = 0.0000), fitness=0.018611812
107.50 secs, 2129 evals, 2040 steps, improv/step: 0.241 (last = 0.0000), fitness=0.018611812
108.01 secs, 2139 evals, 2050 steps, improv/step: 0.240 (last = 0.1000), fitness=0.018611812
108.54 secs, 2149 evals, 2060 steps, improv/step: 0.240 (last = 0.1000), fitness=0.018611812
109.08 secs, 2160 evals, 2071 steps, improv/step: 0.239 (last = 0.0000), fitness=0.018611812
109.62 secs, 2172 evals, 2083 steps, improv/step: 0.238 (last = 0.0833), fitness=0.018611812
110.13 secs, 2183 evals, 2094 steps, improv/step: 0.237 (last = 0.1818), fitness=0.018611812
110.63 secs, 2193 evals, 2104 steps, improv/step: 0.237 (last = 0.1000), fitness=0.018611812
111.15 secs, 2204 evals, 2115 steps, improv/step: 0.236 (last = 0.1818), fitness=0.018611812
111.66 secs, 2215 evals, 2126 steps, improv/step: 0.237 (last = 0.2727), fitness=0.018611812
112.18 secs, 2226 evals, 2137 steps, improv/step: 0.236 (last = 0.0909), fitness=0.018611812
112.73 secs, 2238 evals, 2149 steps, improv/step: 0.236 (last = 0.2500), fitness=0.018019478
113.28 secs, 2250 evals, 2161 steps, improv/step: 0.237 (last = 0.4167), fitness=0.018019478
113.81 secs, 2262 evals, 2173 steps, improv/step: 0.237 (last = 0.1667), fitness=0.018019478
114.34 secs, 2273 evals, 2184 steps, improv/step: 0.236 (last = 0.1818), fitness=0.018019478
114.87 secs, 2285 evals, 2196 steps, improv/step: 0.236 (last = 0.1667), fitness=0.018019478
115.38 secs, 2296 evals, 2207 steps, improv/step: 0.237 (last = 0.3636), fitness=0.018019478
115.88 secs, 2307 evals, 2218 steps, improv/step: 0.236 (last = 0.1818), fitness=0.018019478
116.41 secs, 2319 evals, 2230 steps, improv/step: 0.235 (last = 0.0833), fitness=0.018019478
116.93 secs, 2330 evals, 2241 steps, improv/step: 0.235 (last = 0.0909), fitness=0.018019478
117.45 secs, 2342 evals, 2253 steps, improv/step: 0.235 (last = 0.2500), fitness=0.012552310
117.96 secs, 2353 evals, 2264 steps, improv/step: 0.234 (last = 0.0909), fitness=0.012552310
118.47 secs, 2364 evals, 2275 steps, improv/step: 0.235 (last = 0.3636), fitness=0.012552310
119.00 secs, 2376 evals, 2287 steps, improv/step: 0.235 (last = 0.2500), fitness=0.012552310
119.51 secs, 2387 evals, 2298 steps, improv/step: 0.234 (last = 0.0909), fitness=0.012552310
120.03 secs, 2399 evals, 2310 steps, improv/step: 0.234 (last = 0.1667), fitness=0.012552310
120.58 secs, 2411 evals, 2322 steps, improv/step: 0.233 (last = 0.0000), fitness=0.012552310
121.11 secs, 2421 evals, 2332 steps, improv/step: 0.232 (last = 0.2000), fitness=0.012552310
121.64 secs, 2433 evals, 2344 steps, improv/step: 0.232 (last = 0.0833), fitness=0.012552310
122.17 secs, 2445 evals, 2356 steps, improv/step: 0.231 (last = 0.0833), fitness=0.012552310
122.72 secs, 2454 evals, 2365 steps, improv/step: 0.230 (last = 0.1111), fitness=0.012552310
123.24 secs, 2466 evals, 2377 steps, improv/step: 0.231 (last = 0.3333), fitness=0.012552310
123.77 secs, 2477 evals, 2388 steps, improv/step: 0.230 (last = 0.0909), fitness=0.012552310
124.32 secs, 2484 evals, 2395 steps, improv/step: 0.230 (last = 0.2857), fitness=0.012552310
124.88 secs, 2496 evals, 2407 steps, improv/step: 0.230 (last = 0.1667), fitness=0.011625243
125.40 secs, 2508 evals, 2419 steps, improv/step: 0.231 (last = 0.4167), fitness=0.011625243
125.94 secs, 2518 evals, 2429 steps, improv/step: 0.231 (last = 0.2000), fitness=0.011625243
126.47 secs, 2528 evals, 2439 steps, improv/step: 0.231 (last = 0.2000), fitness=0.011625243
127.02 secs, 2539 evals, 2450 steps, improv/step: 0.230 (last = 0.0000), fitness=0.011625243
127.58 secs, 2549 evals, 2460 steps, improv/step: 0.230 (last = 0.2000), fitness=0.011625243
128.11 secs, 2561 evals, 2472 steps, improv/step: 0.229 (last = 0.1667), fitness=0.011625243
128.66 secs, 2572 evals, 2483 steps, improv/step: 0.230 (last = 0.4545), fitness=0.011625243
129.16 secs, 2583 evals, 2494 steps, improv/step: 0.231 (last = 0.2727), fitness=0.011625243
129.67 secs, 2594 evals, 2505 steps, improv/step: 0.230 (last = 0.0909), fitness=0.011625243
130.19 secs, 2604 evals, 2515 steps, improv/step: 0.229 (last = 0.1000), fitness=0.011625243
130.73 secs, 2615 evals, 2526 steps, improv/step: 0.229 (last = 0.1818), fitness=0.011625243
131.26 secs, 2627 evals, 2538 steps, improv/step: 0.229 (last = 0.2500), fitness=0.010072585
131.80 secs, 2639 evals, 2550 steps, improv/step: 0.229 (last = 0.0833), fitness=0.010072585
132.35 secs, 2650 evals, 2561 steps, improv/step: 0.228 (last = 0.1818), fitness=0.010072585
132.85 secs, 2658 evals, 2569 steps, improv/step: 0.228 (last = 0.0000), fitness=0.010072585
133.38 secs, 2670 evals, 2581 steps, improv/step: 0.227 (last = 0.1667), fitness=0.010072585
133.91 secs, 2681 evals, 2592 steps, improv/step: 0.227 (last = 0.0909), fitness=0.010072585
134.42 secs, 2693 evals, 2604 steps, improv/step: 0.227 (last = 0.1667), fitness=0.010072585
134.94 secs, 2704 evals, 2615 steps, improv/step: 0.227 (last = 0.2727), fitness=0.010072585
135.47 secs, 2716 evals, 2627 steps, improv/step: 0.226 (last = 0.1667), fitness=0.010072585
135.99 secs, 2728 evals, 2640 steps, improv/step: 0.226 (last = 0.0769), fitness=0.010072585
136.52 secs, 2739 evals, 2651 steps, improv/step: 0.226 (last = 0.1818), fitness=0.010072585
137.14 secs, 2750 evals, 2662 steps, improv/step: 0.225 (last = 0.0909), fitness=0.010072585
137.68 secs, 2761 evals, 2673 steps, improv/step: 0.226 (last = 0.4545), fitness=0.010072585
138.23 secs, 2767 evals, 2679 steps, improv/step: 0.225 (last = 0.0000), fitness=0.010072585
138.74 secs, 2778 evals, 2690 steps, improv/step: 0.226 (last = 0.2727), fitness=0.010072585
139.28 secs, 2790 evals, 2702 steps, improv/step: 0.225 (last = 0.1667), fitness=0.009970221
139.80 secs, 2801 evals, 2713 steps, improv/step: 0.226 (last = 0.2727), fitness=0.003726769
140.36 secs, 2805 evals, 2717 steps, improv/step: 0.226 (last = 0.2500), fitness=0.003726769
140.89 secs, 2811 evals, 2723 steps, improv/step: 0.225 (last = 0.1667), fitness=0.003726769
141.41 secs, 2823 evals, 2735 steps, improv/step: 0.226 (last = 0.2500), fitness=0.003726769
141.95 secs, 2835 evals, 2747 steps, improv/step: 0.225 (last = 0.1667), fitness=0.003726769
142.48 secs, 2843 evals, 2755 steps, improv/step: 0.225 (last = 0.0000), fitness=0.003726769
143.01 secs, 2855 evals, 2767 steps, improv/step: 0.225 (last = 0.3333), fitness=0.003726769
143.52 secs, 2866 evals, 2778 steps, improv/step: 0.225 (last = 0.0909), fitness=0.003726769
144.08 secs, 2875 evals, 2787 steps, improv/step: 0.224 (last = 0.1111), fitness=0.003726769
144.61 secs, 2877 evals, 2789 steps, improv/step: 0.224 (last = 0.0000), fitness=0.003726769
145.16 secs, 2880 evals, 2792 steps, improv/step: 0.224 (last = 0.0000), fitness=0.003726769
145.72 secs, 2890 evals, 2802 steps, improv/step: 0.224 (last = 0.2000), fitness=0.003726769
146.26 secs, 2899 evals, 2811 steps, improv/step: 0.223 (last = 0.1111), fitness=0.003726769
146.78 secs, 2911 evals, 2823 steps, improv/step: 0.223 (last = 0.0833), fitness=0.003726769
147.28 secs, 2922 evals, 2834 steps, improv/step: 0.223 (last = 0.2727), fitness=0.003726769
147.82 secs, 2934 evals, 2846 steps, improv/step: 0.222 (last = 0.0833), fitness=0.003726769
148.32 secs, 2945 evals, 2857 steps, improv/step: 0.222 (last = 0.0000), fitness=0.003726769
148.86 secs, 2956 evals, 2868 steps, improv/step: 0.221 (last = 0.1818), fitness=0.003726769
149.36 secs, 2966 evals, 2878 steps, improv/step: 0.221 (last = 0.1000), fitness=0.003726769
149.90 secs, 2978 evals, 2890 steps, improv/step: 0.220 (last = 0.0833), fitness=0.003726769
150.41 secs, 2989 evals, 2901 steps, improv/step: 0.220 (last = 0.0000), fitness=0.003726769
150.95 secs, 3001 evals, 2913 steps, improv/step: 0.219 (last = 0.0000), fitness=0.003726769
151.46 secs, 3012 evals, 2924 steps, improv/step: 0.219 (last = 0.2727), fitness=0.003726769
151.97 secs, 3023 evals, 2935 steps, improv/step: 0.219 (last = 0.1818), fitness=0.003726769
152.50 secs, 3035 evals, 2947 steps, improv/step: 0.218 (last = 0.0833), fitness=0.003726769
153.03 secs, 3047 evals, 2959 steps, improv/step: 0.219 (last = 0.5000), fitness=0.003726769
153.58 secs, 3058 evals, 2970 steps, improv/step: 0.219 (last = 0.0909), fitness=0.003726769
154.12 secs, 3070 evals, 2982 steps, improv/step: 0.219 (last = 0.1667), fitness=0.003726769
154.64 secs, 3081 evals, 2993 steps, improv/step: 0.219 (last = 0.1818), fitness=0.003726769
155.17 secs, 3093 evals, 3005 steps, improv/step: 0.218 (last = 0.0000), fitness=0.003726769
155.71 secs, 3105 evals, 3017 steps, improv/step: 0.217 (last = 0.1667), fitness=0.003726769
156.22 secs, 3116 evals, 3028 steps, improv/step: 0.218 (last = 0.3636), fitness=0.003726769
156.72 secs, 3127 evals, 3039 steps, improv/step: 0.218 (last = 0.1818), fitness=0.003726769
157.23 secs, 3139 evals, 3051 steps, improv/step: 0.217 (last = 0.0000), fitness=0.003726769
157.78 secs, 3151 evals, 3063 steps, improv/step: 0.217 (last = 0.3333), fitness=0.003726769
158.30 secs, 3163 evals, 3075 steps, improv/step: 0.217 (last = 0.1667), fitness=0.003726769
158.82 secs, 3174 evals, 3086 steps, improv/step: 0.217 (last = 0.2727), fitness=0.003726769
159.35 secs, 3186 evals, 3098 steps, improv/step: 0.217 (last = 0.1667), fitness=0.003726769
159.88 secs, 3198 evals, 3110 steps, improv/step: 0.217 (last = 0.2500), fitness=0.003726769
160.40 secs, 3210 evals, 3122 steps, improv/step: 0.217 (last = 0.1667), fitness=0.003726769
160.92 secs, 3221 evals, 3133 steps, improv/step: 0.217 (last = 0.1818), fitness=0.003726769
161.43 secs, 3232 evals, 3144 steps, improv/step: 0.217 (last = 0.2727), fitness=0.003726769
161.96 secs, 3244 evals, 3156 steps, improv/step: 0.217 (last = 0.0833), fitness=0.003726769
162.48 secs, 3256 evals, 3168 steps, improv/step: 0.216 (last = 0.0000), fitness=0.003726769
163.00 secs, 3268 evals, 3180 steps, improv/step: 0.216 (last = 0.2500), fitness=0.003726769
163.50 secs, 3279 evals, 3191 steps, improv/step: 0.216 (last = 0.2727), fitness=0.003726769
164.01 secs, 3290 evals, 3202 steps, improv/step: 0.216 (last = 0.1818), fitness=0.003726769
164.54 secs, 3301 evals, 3213 steps, improv/step: 0.215 (last = 0.0000), fitness=0.003726769
165.05 secs, 3312 evals, 3224 steps, improv/step: 0.215 (last = 0.0000), fitness=0.003726769
165.59 secs, 3324 evals, 3236 steps, improv/step: 0.214 (last = 0.1667), fitness=0.003726769
166.12 secs, 3333 evals, 3245 steps, improv/step: 0.214 (last = 0.1111), fitness=0.003726769
166.63 secs, 3344 evals, 3256 steps, improv/step: 0.213 (last = 0.0000), fitness=0.003726769
167.20 secs, 3350 evals, 3262 steps, improv/step: 0.213 (last = 0.1667), fitness=0.003726769
167.72 secs, 3362 evals, 3274 steps, improv/step: 0.213 (last = 0.1667), fitness=0.003726769
168.25 secs, 3374 evals, 3286 steps, improv/step: 0.213 (last = 0.1667), fitness=0.003726769
168.78 secs, 3385 evals, 3297 steps, improv/step: 0.213 (last = 0.0909), fitness=0.003726769
169.31 secs, 3396 evals, 3308 steps, improv/step: 0.213 (last = 0.3636), fitness=0.003726769
169.83 secs, 3405 evals, 3317 steps, improv/step: 0.213 (last = 0.0000), fitness=0.003726769
170.36 secs, 3414 evals, 3326 steps, improv/step: 0.213 (last = 0.2222), fitness=0.003726769
170.88 secs, 3423 evals, 3335 steps, improv/step: 0.212 (last = 0.1111), fitness=0.003726769
171.42 secs, 3435 evals, 3347 steps, improv/step: 0.212 (last = 0.0833), fitness=0.003726769
171.93 secs, 3447 evals, 3359 steps, improv/step: 0.212 (last = 0.1667), fitness=0.003726769
172.48 secs, 3459 evals, 3371 steps, improv/step: 0.212 (last = 0.1667), fitness=0.003726769
173.01 secs, 3466 evals, 3378 steps, improv/step: 0.211 (last = 0.1429), fitness=0.003726769
173.63 secs, 3470 evals, 3382 steps, improv/step: 0.211 (last = 0.2500), fitness=0.003726769
174.15 secs, 3480 evals, 3392 steps, improv/step: 0.211 (last = 0.0000), fitness=0.003726769
174.67 secs, 3491 evals, 3403 steps, improv/step: 0.211 (last = 0.2727), fitness=0.003726769
175.19 secs, 3500 evals, 3412 steps, improv/step: 0.211 (last = 0.2222), fitness=0.003726769
175.70 secs, 3510 evals, 3422 steps, improv/step: 0.211 (last = 0.2000), fitness=0.003726769
176.20 secs, 3521 evals, 3433 steps, improv/step: 0.211 (last = 0.0909), fitness=0.003726769
176.71 secs, 3530 evals, 3442 steps, improv/step: 0.210 (last = 0.1111), fitness=0.003726769
177.22 secs, 3541 evals, 3453 steps, improv/step: 0.211 (last = 0.2727), fitness=0.003726769
177.78 secs, 3551 evals, 3463 steps, improv/step: 0.210 (last = 0.0000), fitness=0.003726769
178.29 secs, 3562 evals, 3474 steps, improv/step: 0.210 (last = 0.2727), fitness=0.003726769
178.83 secs, 3574 evals, 3486 steps, improv/step: 0.210 (last = 0.0833), fitness=0.003726769
179.35 secs, 3586 evals, 3498 steps, improv/step: 0.210 (last = 0.2500), fitness=0.003726769
179.88 secs, 3598 evals, 3510 steps, improv/step: 0.210 (last = 0.1667), fitness=0.003726769
180.41 secs, 3610 evals, 3522 steps, improv/step: 0.209 (last = 0.0000), fitness=0.003726769
180.95 secs, 3619 evals, 3531 steps, improv/step: 0.208 (last = 0.0000), fitness=0.003726769
181.50 secs, 3630 evals, 3542 steps, improv/step: 0.208 (last = 0.0909), fitness=0.003726769
182.02 secs, 3642 evals, 3554 steps, improv/step: 0.208 (last = 0.1667), fitness=0.003726769
182.56 secs, 3654 evals, 3566 steps, improv/step: 0.208 (last = 0.1667), fitness=0.003726769
183.08 secs, 3666 evals, 3578 steps, improv/step: 0.208 (last = 0.1667), fitness=0.003726769
183.59 secs, 3677 evals, 3589 steps, improv/step: 0.207 (last = 0.0909), fitness=0.003726769
184.11 secs, 3689 evals, 3601 steps, improv/step: 0.207 (last = 0.1667), fitness=0.003726769
184.62 secs, 3699 evals, 3611 steps, improv/step: 0.207 (last = 0.0000), fitness=0.003726769
185.13 secs, 3710 evals, 3622 steps, improv/step: 0.206 (last = 0.0000), fitness=0.003726769
185.65 secs, 3722 evals, 3634 steps, improv/step: 0.205 (last = 0.0000), fitness=0.003726769
186.19 secs, 3734 evals, 3646 steps, improv/step: 0.205 (last = 0.1667), fitness=0.003726769
186.70 secs, 3745 evals, 3657 steps, improv/step: 0.205 (last = 0.0000), fitness=0.003726769
187.20 secs, 3753 evals, 3665 steps, improv/step: 0.205 (last = 0.3750), fitness=0.003726769
187.73 secs, 3765 evals, 3677 steps, improv/step: 0.205 (last = 0.1667), fitness=0.003726769
188.28 secs, 3777 evals, 3689 steps, improv/step: 0.204 (last = 0.0833), fitness=0.003726769
188.79 secs, 3789 evals, 3701 steps, improv/step: 0.204 (last = 0.0833), fitness=0.003726769
189.32 secs, 3801 evals, 3713 steps, improv/step: 0.204 (last = 0.1667), fitness=0.003694383
189.83 secs, 3813 evals, 3725 steps, improv/step: 0.204 (last = 0.1667), fitness=0.003694383
190.34 secs, 3824 evals, 3736 steps, improv/step: 0.203 (last = 0.0000), fitness=0.003694383
190.85 secs, 3836 evals, 3748 steps, improv/step: 0.203 (last = 0.1667), fitness=0.003694383
191.39 secs, 3848 evals, 3760 steps, improv/step: 0.203 (last = 0.1667), fitness=0.003694383
191.91 secs, 3860 evals, 3772 steps, improv/step: 0.204 (last = 0.4167), fitness=0.003694383
192.43 secs, 3872 evals, 3784 steps, improv/step: 0.203 (last = 0.0000), fitness=0.003694383
192.96 secs, 3884 evals, 3796 steps, improv/step: 0.203 (last = 0.0833), fitness=0.003694383
193.49 secs, 3895 evals, 3807 steps, improv/step: 0.202 (last = 0.0000), fitness=0.003694383
194.00 secs, 3903 evals, 3815 steps, improv/step: 0.202 (last = 0.0000), fitness=0.003694383
194.52 secs, 3913 evals, 3825 steps, improv/step: 0.202 (last = 0.2000), fitness=0.003694383
195.06 secs, 3920 evals, 3832 steps, improv/step: 0.201 (last = 0.1429), fitness=0.003694383
195.56 secs, 3930 evals, 3842 steps, improv/step: 0.201 (last = 0.1000), fitness=0.003694383
196.09 secs, 3937 evals, 3849 steps, improv/step: 0.201 (last = 0.0000), fitness=0.003694383
196.63 secs, 3947 evals, 3859 steps, improv/step: 0.200 (last = 0.0000), fitness=0.003694383
197.14 secs, 3954 evals, 3866 steps, improv/step: 0.200 (last = 0.0000), fitness=0.003694383
197.71 secs, 3964 evals, 3876 steps, improv/step: 0.199 (last = 0.0000), fitness=0.003694383
198.26 secs, 3969 evals, 3881 steps, improv/step: 0.199 (last = 0.0000), fitness=0.003694383
198.80 secs, 3977 evals, 3889 steps, improv/step: 0.200 (last = 0.3750), fitness=0.003694383
199.34 secs, 3985 evals, 3897 steps, improv/step: 0.200 (last = 0.2500), fitness=0.003694383
199.85 secs, 3996 evals, 3908 steps, improv/step: 0.199 (last = 0.0909), fitness=0.003694383
200.39 secs, 4007 evals, 3919 steps, improv/step: 0.199 (last = 0.1818), fitness=0.003694383
200.92 secs, 4019 evals, 3931 steps, improv/step: 0.199 (last = 0.1667), fitness=0.003694383
201.45 secs, 4030 evals, 3942 steps, improv/step: 0.200 (last = 0.3636), fitness=0.003694383
201.98 secs, 4041 evals, 3953 steps, improv/step: 0.200 (last = 0.1818), fitness=0.003694383
202.48 secs, 4052 evals, 3964 steps, improv/step: 0.199 (last = 0.0909), fitness=0.003694383
203.00 secs, 4064 evals, 3976 steps, improv/step: 0.199 (last = 0.0000), fitness=0.003694383
203.52 secs, 4075 evals, 3987 steps, improv/step: 0.199 (last = 0.2727), fitness=0.003694383
204.06 secs, 4087 evals, 3999 steps, improv/step: 0.199 (last = 0.1667), fitness=0.003694383
204.59 secs, 4098 evals, 4010 steps, improv/step: 0.199 (last = 0.1818), fitness=0.003694383
205.19 secs, 4109 evals, 4021 steps, improv/step: 0.199 (last = 0.2727), fitness=0.003694383
205.75 secs, 4116 evals, 4028 steps, improv/step: 0.199 (last = 0.1429), fitness=0.003694383
206.29 secs, 4128 evals, 4040 steps, improv/step: 0.199 (last = 0.3333), fitness=0.003694383
206.83 secs, 4140 evals, 4052 steps, improv/step: 0.199 (last = 0.0833), fitness=0.003694383
207.33 secs, 4150 evals, 4062 steps, improv/step: 0.199 (last = 0.2000), fitness=0.003694383
207.88 secs, 4161 evals, 4073 steps, improv/step: 0.199 (last = 0.1818), fitness=0.003694383
208.39 secs, 4173 evals, 4085 steps, improv/step: 0.199 (last = 0.2500), fitness=0.003628942
208.91 secs, 4184 evals, 4096 steps, improv/step: 0.199 (last = 0.0909), fitness=0.003628942
209.45 secs, 4196 evals, 4108 steps, improv/step: 0.198 (last = 0.0000), fitness=0.003628942
209.99 secs, 4207 evals, 4119 steps, improv/step: 0.198 (last = 0.0909), fitness=0.003628942
210.49 secs, 4218 evals, 4130 steps, improv/step: 0.198 (last = 0.0909), fitness=0.003628942
211.00 secs, 4230 evals, 4142 steps, improv/step: 0.198 (last = 0.2500), fitness=0.003628942
211.50 secs, 4241 evals, 4153 steps, improv/step: 0.197 (last = 0.0909), fitness=0.003628942
212.03 secs, 4252 evals, 4164 steps, improv/step: 0.197 (last = 0.0000), fitness=0.003628942
212.55 secs, 4264 evals, 4176 steps, improv/step: 0.197 (last = 0.0833), fitness=0.003628942
213.08 secs, 4276 evals, 4188 steps, improv/step: 0.196 (last = 0.0000), fitness=0.003628942
213.60 secs, 4288 evals, 4200 steps, improv/step: 0.196 (last = 0.1667), fitness=0.003167636
214.12 secs, 4299 evals, 4211 steps, improv/step: 0.196 (last = 0.1818), fitness=0.003167636
214.65 secs, 4311 evals, 4223 steps, improv/step: 0.196 (last = 0.0833), fitness=0.003167636
215.20 secs, 4321 evals, 4233 steps, improv/step: 0.195 (last = 0.1000), fitness=0.003167636
215.71 secs, 4332 evals, 4244 steps, improv/step: 0.196 (last = 0.2727), fitness=0.002648796
216.22 secs, 4344 evals, 4256 steps, improv/step: 0.195 (last = 0.0833), fitness=0.002648796
216.75 secs, 4354 evals, 4266 steps, improv/step: 0.195 (last = 0.0000), fitness=0.002648796
217.27 secs, 4365 evals, 4277 steps, improv/step: 0.195 (last = 0.1818), fitness=0.002648796
217.78 secs, 4377 evals, 4289 steps, improv/step: 0.194 (last = 0.0833), fitness=0.002648796
218.32 secs, 4389 evals, 4301 steps, improv/step: 0.195 (last = 0.3333), fitness=0.002648796
218.85 secs, 4401 evals, 4313 steps, improv/step: 0.194 (last = 0.0000), fitness=0.002648796
219.38 secs, 4413 evals, 4325 steps, improv/step: 0.194 (last = 0.2500), fitness=0.002648796
219.90 secs, 4425 evals, 4337 steps, improv/step: 0.194 (last = 0.0833), fitness=0.002648796
220.44 secs, 4437 evals, 4349 steps, improv/step: 0.194 (last = 0.1667), fitness=0.002648796
220.96 secs, 4449 evals, 4361 steps, improv/step: 0.194 (last = 0.0833), fitness=0.002648796
221.46 secs, 4460 evals, 4372 steps, improv/step: 0.194 (last = 0.0909), fitness=0.002648796
221.98 secs, 4472 evals, 4384 steps, improv/step: 0.193 (last = 0.0833), fitness=0.002648796
222.50 secs, 4482 evals, 4394 steps, improv/step: 0.193 (last = 0.1000), fitness=0.002517625
223.03 secs, 4494 evals, 4406 steps, improv/step: 0.193 (last = 0.0833), fitness=0.002517625
223.56 secs, 4505 evals, 4417 steps, improv/step: 0.193 (last = 0.2727), fitness=0.002517625
224.07 secs, 4516 evals, 4428 steps, improv/step: 0.193 (last = 0.0909), fitness=0.002517625
224.60 secs, 4528 evals, 4440 steps, improv/step: 0.192 (last = 0.0833), fitness=0.002517625
225.13 secs, 4540 evals, 4452 steps, improv/step: 0.192 (last = 0.0833), fitness=0.002517625
225.64 secs, 4551 evals, 4463 steps, improv/step: 0.192 (last = 0.1818), fitness=0.002517625
226.16 secs, 4563 evals, 4475 steps, improv/step: 0.192 (last = 0.0833), fitness=0.002135942
226.67 secs, 4574 evals, 4486 steps, improv/step: 0.191 (last = 0.0909), fitness=0.002135942
227.20 secs, 4586 evals, 4498 steps, improv/step: 0.192 (last = 0.3333), fitness=0.002135942
227.75 secs, 4598 evals, 4510 steps, improv/step: 0.192 (last = 0.0833), fitness=0.002135942
228.26 secs, 4610 evals, 4522 steps, improv/step: 0.192 (last = 0.2500), fitness=0.002135942
228.78 secs, 4621 evals, 4533 steps, improv/step: 0.192 (last = 0.1818), fitness=0.002135942
229.31 secs, 4632 evals, 4544 steps, improv/step: 0.192 (last = 0.1818), fitness=0.002135942
229.84 secs, 4643 evals, 4555 steps, improv/step: 0.192 (last = 0.2727), fitness=0.002135942
230.38 secs, 4655 evals, 4567 steps, improv/step: 0.192 (last = 0.1667), fitness=0.002135942
230.88 secs, 4667 evals, 4579 steps, improv/step: 0.192 (last = 0.2500), fitness=0.001631454
231.41 secs, 4677 evals, 4589 steps, improv/step: 0.192 (last = 0.4000), fitness=0.001631454
231.95 secs, 4687 evals, 4599 steps, improv/step: 0.192 (last = 0.1000), fitness=0.001631454
232.45 secs, 4696 evals, 4608 steps, improv/step: 0.192 (last = 0.1111), fitness=0.001631454
232.99 secs, 4706 evals, 4618 steps, improv/step: 0.192 (last = 0.2000), fitness=0.001631454
233.50 secs, 4715 evals, 4627 steps, improv/step: 0.192 (last = 0.0000), fitness=0.001631454
234.03 secs, 4726 evals, 4638 steps, improv/step: 0.191 (last = 0.0909), fitness=0.001631454
234.56 secs, 4738 evals, 4650 steps, improv/step: 0.191 (last = 0.1667), fitness=0.001631454
235.10 secs, 4750 evals, 4662 steps, improv/step: 0.191 (last = 0.1667), fitness=0.001631454
235.62 secs, 4762 evals, 4674 steps, improv/step: 0.191 (last = 0.0833), fitness=0.001631454
236.15 secs, 4774 evals, 4686 steps, improv/step: 0.191 (last = 0.1667), fitness=0.001631454
236.66 secs, 4785 evals, 4697 steps, improv/step: 0.191 (last = 0.2727), fitness=0.001631454
237.20 secs, 4795 evals, 4707 steps, improv/step: 0.191 (last = 0.1000), fitness=0.001631454
237.74 secs, 4807 evals, 4719 steps, improv/step: 0.191 (last = 0.2500), fitness=0.001631454
238.27 secs, 4819 evals, 4731 steps, improv/step: 0.191 (last = 0.0833), fitness=0.001631454
238.81 secs, 4831 evals, 4743 steps, improv/step: 0.190 (last = 0.0000), fitness=0.001631454
239.33 secs, 4843 evals, 4755 steps, improv/step: 0.190 (last = 0.0833), fitness=0.001631454
239.85 secs, 4854 evals, 4766 steps, improv/step: 0.190 (last = 0.0909), fitness=0.001631454
240.36 secs, 4864 evals, 4776 steps, improv/step: 0.189 (last = 0.0000), fitness=0.001631454
240.89 secs, 4875 evals, 4787 steps, improv/step: 0.189 (last = 0.1818), fitness=0.001631454
241.41 secs, 4887 evals, 4799 steps, improv/step: 0.189 (last = 0.0000), fitness=0.001631454
241.94 secs, 4897 evals, 4809 steps, improv/step: 0.189 (last = 0.1000), fitness=0.001631454
242.47 secs, 4907 evals, 4819 steps, improv/step: 0.189 (last = 0.2000), fitness=0.001631454
243.00 secs, 4919 evals, 4831 steps, improv/step: 0.189 (last = 0.0833), fitness=0.001631454
243.53 secs, 4931 evals, 4843 steps, improv/step: 0.189 (last = 0.1667), fitness=0.001631454
244.06 secs, 4943 evals, 4855 steps, improv/step: 0.188 (last = 0.0000), fitness=0.001631454
244.62 secs, 4954 evals, 4866 steps, improv/step: 0.188 (last = 0.0909), fitness=0.001631454
245.15 secs, 4966 evals, 4878 steps, improv/step: 0.188 (last = 0.1667), fitness=0.001631454
245.69 secs, 4978 evals, 4890 steps, improv/step: 0.188 (last = 0.0833), fitness=0.001631454
246.20 secs, 4990 evals, 4902 steps, improv/step: 0.187 (last = 0.0000), fitness=0.001631454
246.70 secs, 5000 evals, 4912 steps, improv/step: 0.187 (last = 0.0000), fitness=0.001631454
247.25 secs, 5011 evals, 4923 steps, improv/step: 0.187 (last = 0.1818), fitness=0.001631454
247.76 secs, 5023 evals, 4935 steps, improv/step: 0.186 (last = 0.0000), fitness=0.001631454
248.30 secs, 5035 evals, 4947 steps, improv/step: 0.186 (last = 0.1667), fitness=0.001631454
248.81 secs, 5047 evals, 4959 steps, improv/step: 0.186 (last = 0.1667), fitness=0.001631454
249.35 secs, 5059 evals, 4971 steps, improv/step: 0.186 (last = 0.1667), fitness=0.001631454
249.88 secs, 5070 evals, 4982 steps, improv/step: 0.186 (last = 0.0000), fitness=0.001631454
250.40 secs, 5082 evals, 4994 steps, improv/step: 0.185 (last = 0.0833), fitness=0.001631454
250.91 secs, 5092 evals, 5004 steps, improv/step: 0.185 (last = 0.1000), fitness=0.001631454
251.42 secs, 5104 evals, 5016 steps, improv/step: 0.185 (last = 0.2500), fitness=0.001631454
251.96 secs, 5116 evals, 5028 steps, improv/step: 0.185 (last = 0.1667), fitness=0.001631454
252.49 secs, 5127 evals, 5039 steps, improv/step: 0.185 (last = 0.0000), fitness=0.001631454
253.01 secs, 5138 evals, 5050 steps, improv/step: 0.185 (last = 0.0000), fitness=0.001631454
253.55 secs, 5149 evals, 5061 steps, improv/step: 0.184 (last = 0.0000), fitness=0.001631454
254.09 secs, 5160 evals, 5072 steps, improv/step: 0.184 (last = 0.0909), fitness=0.001631454
254.62 secs, 5171 evals, 5083 steps, improv/step: 0.184 (last = 0.0000), fitness=0.001631454
255.13 secs, 5182 evals, 5094 steps, improv/step: 0.183 (last = 0.0909), fitness=0.001631454
255.64 secs, 5194 evals, 5106 steps, improv/step: 0.183 (last = 0.0833), fitness=0.001631454
256.18 secs, 5205 evals, 5117 steps, improv/step: 0.183 (last = 0.2727), fitness=0.001631454
256.72 secs, 5217 evals, 5129 steps, improv/step: 0.183 (last = 0.1667), fitness=0.001631454
257.22 secs, 5228 evals, 5140 steps, improv/step: 0.183 (last = 0.1818), fitness=0.001631454
257.76 secs, 5240 evals, 5152 steps, improv/step: 0.183 (last = 0.0833), fitness=0.001631454
258.27 secs, 5252 evals, 5164 steps, improv/step: 0.183 (last = 0.1667), fitness=0.001631454
258.79 secs, 5264 evals, 5176 steps, improv/step: 0.183 (last = 0.2500), fitness=0.001631454
259.32 secs, 5276 evals, 5188 steps, improv/step: 0.183 (last = 0.0833), fitness=0.001631454
259.85 secs, 5288 evals, 5200 steps, improv/step: 0.183 (last = 0.0833), fitness=0.001631454
260.36 secs, 5300 evals, 5212 steps, improv/step: 0.182 (last = 0.0833), fitness=0.001631454
260.91 secs, 5311 evals, 5223 steps, improv/step: 0.182 (last = 0.1818), fitness=0.001631454
261.43 secs, 5322 evals, 5234 steps, improv/step: 0.182 (last = 0.0000), fitness=0.001631454
261.95 secs, 5333 evals, 5245 steps, improv/step: 0.182 (last = 0.0909), fitness=0.001631454
262.48 secs, 5345 evals, 5257 steps, improv/step: 0.182 (last = 0.2500), fitness=0.001631454
263.01 secs, 5357 evals, 5269 steps, improv/step: 0.182 (last = 0.0000), fitness=0.001631454
263.53 secs, 5369 evals, 5281 steps, improv/step: 0.182 (last = 0.1667), fitness=0.001620025
264.05 secs, 5381 evals, 5293 steps, improv/step: 0.181 (last = 0.0000), fitness=0.001620025
264.56 secs, 5392 evals, 5304 steps, improv/step: 0.181 (last = 0.0909), fitness=0.001620025
265.08 secs, 5404 evals, 5316 steps, improv/step: 0.181 (last = 0.1667), fitness=0.001551697
265.61 secs, 5416 evals, 5328 steps, improv/step: 0.181 (last = 0.0000), fitness=0.001551697
266.19 secs, 5424 evals, 5336 steps, improv/step: 0.180 (last = 0.0000), fitness=0.001551697
266.72 secs, 5432 evals, 5344 steps, improv/step: 0.180 (last = 0.2500), fitness=0.001551697
267.26 secs, 5444 evals, 5356 steps, improv/step: 0.180 (last = 0.0000), fitness=0.001551697
267.77 secs, 5456 evals, 5368 steps, improv/step: 0.180 (last = 0.0000), fitness=0.001551697
268.30 secs, 5468 evals, 5380 steps, improv/step: 0.179 (last = 0.0000), fitness=0.001551697
268.83 secs, 5479 evals, 5391 steps, improv/step: 0.179 (last = 0.1818), fitness=0.001551697
269.38 secs, 5491 evals, 5403 steps, improv/step: 0.179 (last = 0.0833), fitness=0.001551697
269.90 secs, 5503 evals, 5415 steps, improv/step: 0.179 (last = 0.0833), fitness=0.001551697
270.44 secs, 5515 evals, 5428 steps, improv/step: 0.179 (last = 0.1538), fitness=0.001551697
270.97 secs, 5526 evals, 5439 steps, improv/step: 0.178 (last = 0.0000), fitness=0.001551697
271.49 secs, 5537 evals, 5450 steps, improv/step: 0.178 (last = 0.0000), fitness=0.001551697
272.00 secs, 5548 evals, 5461 steps, improv/step: 0.178 (last = 0.1818), fitness=0.001551697
272.51 secs, 5558 evals, 5471 steps, improv/step: 0.178 (last = 0.3000), fitness=0.001378124
273.04 secs, 5570 evals, 5483 steps, improv/step: 0.178 (last = 0.1667), fitness=0.001378124
273.57 secs, 5582 evals, 5495 steps, improv/step: 0.178 (last = 0.0833), fitness=0.001378124
274.09 secs, 5594 evals, 5507 steps, improv/step: 0.178 (last = 0.0833), fitness=0.001378124
274.64 secs, 5605 evals, 5518 steps, improv/step: 0.178 (last = 0.2727), fitness=0.001378124
275.16 secs, 5617 evals, 5530 steps, improv/step: 0.178 (last = 0.3333), fitness=0.001378124
275.68 secs, 5626 evals, 5539 steps, improv/step: 0.178 (last = 0.1111), fitness=0.001378124
276.19 secs, 5635 evals, 5548 steps, improv/step: 0.178 (last = 0.2222), fitness=0.001378124
276.71 secs, 5646 evals, 5559 steps, improv/step: 0.178 (last = 0.0909), fitness=0.001378124
277.23 secs, 5657 evals, 5570 steps, improv/step: 0.178 (last = 0.1818), fitness=0.001378124
277.76 secs, 5669 evals, 5582 steps, improv/step: 0.178 (last = 0.0000), fitness=0.001378124
278.30 secs, 5680 evals, 5593 steps, improv/step: 0.178 (last = 0.1818), fitness=0.001282965
278.83 secs, 5691 evals, 5604 steps, improv/step: 0.178 (last = 0.0909), fitness=0.001282965
279.37 secs, 5703 evals, 5616 steps, improv/step: 0.177 (last = 0.0000), fitness=0.001282965
279.88 secs, 5714 evals, 5627 steps, improv/step: 0.177 (last = 0.2727), fitness=0.001282965
280.39 secs, 5723 evals, 5636 steps, improv/step: 0.177 (last = 0.0000), fitness=0.001282965
280.92 secs, 5734 evals, 5647 steps, improv/step: 0.177 (last = 0.0909), fitness=0.001282965
281.47 secs, 5746 evals, 5659 steps, improv/step: 0.177 (last = 0.0000), fitness=0.001282965
282.02 secs, 5757 evals, 5670 steps, improv/step: 0.177 (last = 0.1818), fitness=0.001205989
282.53 secs, 5768 evals, 5681 steps, improv/step: 0.177 (last = 0.1818), fitness=0.001205989
283.07 secs, 5780 evals, 5693 steps, improv/step: 0.176 (last = 0.0000), fitness=0.001205989
283.57 secs, 5791 evals, 5704 steps, improv/step: 0.176 (last = 0.0000), fitness=0.001205989
284.09 secs, 5799 evals, 5712 steps, improv/step: 0.176 (last = 0.3750), fitness=0.000966995
284.63 secs, 5811 evals, 5724 steps, improv/step: 0.176 (last = 0.1667), fitness=0.000966995
285.17 secs, 5823 evals, 5736 steps, improv/step: 0.176 (last = 0.1667), fitness=0.000966995
285.68 secs, 5829 evals, 5742 steps, improv/step: 0.176 (last = 0.0000), fitness=0.000966995
286.19 secs, 5837 evals, 5750 steps, improv/step: 0.176 (last = 0.2500), fitness=0.000966995
286.83 secs, 5846 evals, 5759 steps, improv/step: 0.176 (last = 0.3333), fitness=0.000966995
287.34 secs, 5856 evals, 5769 steps, improv/step: 0.176 (last = 0.1000), fitness=0.000966995
287.86 secs, 5868 evals, 5781 steps, improv/step: 0.176 (last = 0.3333), fitness=0.000966995
288.37 secs, 5879 evals, 5792 steps, improv/step: 0.177 (last = 0.3636), fitness=0.000966995
288.90 secs, 5890 evals, 5803 steps, improv/step: 0.176 (last = 0.0000), fitness=0.000966995
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289.93 secs, 5907 evals, 5820 steps, improv/step: 0.176 (last = 0.2000), fitness=0.000966995
290.53 secs, 5912 evals, 5825 steps, improv/step: 0.176 (last = 0.2000), fitness=0.000966995
291.04 secs, 5919 evals, 5832 steps, improv/step: 0.176 (last = 0.0000), fitness=0.000966995
291.59 secs, 5928 evals, 5841 steps, improv/step: 0.176 (last = 0.1111), fitness=0.000966995
292.17 secs, 5937 evals, 5850 steps, improv/step: 0.176 (last = 0.2222), fitness=0.000966995
292.67 secs, 5945 evals, 5858 steps, improv/step: 0.176 (last = 0.1250), fitness=0.000966995
293.18 secs, 5953 evals, 5866 steps, improv/step: 0.176 (last = 0.0000), fitness=0.000966995
293.77 secs, 5962 evals, 5875 steps, improv/step: 0.176 (last = 0.0000), fitness=0.000966995
294.32 secs, 5971 evals, 5884 steps, improv/step: 0.176 (last = 0.2222), fitness=0.000966995
294.85 secs, 5979 evals, 5892 steps, improv/step: 0.176 (last = 0.1250), fitness=0.000966995
295.38 secs, 5986 evals, 5899 steps, improv/step: 0.176 (last = 0.2857), fitness=0.000966995
295.92 secs, 5997 evals, 5910 steps, improv/step: 0.176 (last = 0.0909), fitness=0.000966995
296.46 secs, 6007 evals, 5920 steps, improv/step: 0.176 (last = 0.1000), fitness=0.000966995
296.98 secs, 6015 evals, 5928 steps, improv/step: 0.176 (last = 0.3750), fitness=0.000966995
297.51 secs, 6027 evals, 5940 steps, improv/step: 0.176 (last = 0.1667), fitness=0.000966995
298.04 secs, 6039 evals, 5952 steps, improv/step: 0.176 (last = 0.2500), fitness=0.000966995
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299.08 secs, 6061 evals, 5974 steps, improv/step: 0.176 (last = 0.0000), fitness=0.000966995
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303.31 secs, 6157 evals, 6070 steps, improv/step: 0.175 (last = 0.1667), fitness=0.000966995
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314.28 secs, 6399 evals, 6312 steps, improv/step: 0.174 (last = 0.1818), fitness=0.000643007
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315.83 secs, 6435 evals, 6348 steps, improv/step: 0.174 (last = 0.2500), fitness=0.000643007
316.36 secs, 6447 evals, 6360 steps, improv/step: 0.174 (last = 0.2500), fitness=0.000643007
316.88 secs, 6459 evals, 6372 steps, improv/step: 0.175 (last = 0.2500), fitness=0.000643007
317.41 secs, 6471 evals, 6384 steps, improv/step: 0.175 (last = 0.3333), fitness=0.000580046
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318.96 secs, 6506 evals, 6419 steps, improv/step: 0.174 (last = 0.0833), fitness=0.000580046
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321.07 secs, 6553 evals, 6466 steps, improv/step: 0.174 (last = 0.2500), fitness=0.000580046
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322.10 secs, 6574 evals, 6487 steps, improv/step: 0.174 (last = 0.0833), fitness=0.000580046
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323.15 secs, 6598 evals, 6511 steps, improv/step: 0.174 (last = 0.3333), fitness=0.000580046
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324.24 secs, 6621 evals, 6534 steps, improv/step: 0.174 (last = 0.1667), fitness=0.000580046
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325.25 secs, 6640 evals, 6553 steps, improv/step: 0.174 (last = 0.0909), fitness=0.000580046
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326.91 secs, 6670 evals, 6583 steps, improv/step: 0.174 (last = 0.2222), fitness=0.000576659
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329.00 secs, 6711 evals, 6624 steps, improv/step: 0.174 (last = 0.0833), fitness=0.000442841
329.51 secs, 6722 evals, 6635 steps, improv/step: 0.174 (last = 0.1818), fitness=0.000442841
330.02 secs, 6733 evals, 6646 steps, improv/step: 0.174 (last = 0.1818), fitness=0.000442841
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331.08 secs, 6756 evals, 6669 steps, improv/step: 0.174 (last = 0.0909), fitness=0.000340176
331.61 secs, 6768 evals, 6681 steps, improv/step: 0.173 (last = 0.0000), fitness=0.000340176
332.15 secs, 6780 evals, 6693 steps, improv/step: 0.173 (last = 0.1667), fitness=0.000340176
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333.19 secs, 6803 evals, 6716 steps, improv/step: 0.173 (last = 0.0909), fitness=0.000340176
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335.25 secs, 6848 evals, 6761 steps, improv/step: 0.173 (last = 0.0909), fitness=0.000340176
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336.26 secs, 6870 evals, 6783 steps, improv/step: 0.172 (last = 0.0909), fitness=0.000340176
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337.84 secs, 6901 evals, 6814 steps, improv/step: 0.172 (last = 0.2000), fitness=0.000340176
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340.51 secs, 6953 evals, 6866 steps, improv/step: 0.171 (last = 0.0000), fitness=0.000340176
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342.64 secs, 6996 evals, 6909 steps, improv/step: 0.171 (last = 0.1667), fitness=0.000340176
343.19 secs, 7008 evals, 6921 steps, improv/step: 0.171 (last = 0.0833), fitness=0.000340176
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344.25 secs, 7031 evals, 6944 steps, improv/step: 0.171 (last = 0.1818), fitness=0.000315121
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347.46 secs, 7082 evals, 6995 steps, improv/step: 0.170 (last = 0.0909), fitness=0.000315121
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349.05 secs, 7118 evals, 7031 steps, improv/step: 0.170 (last = 0.0833), fitness=0.000315121
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350.09 secs, 7141 evals, 7054 steps, improv/step: 0.170 (last = 0.0833), fitness=0.000315121
350.63 secs, 7153 evals, 7066 steps, improv/step: 0.170 (last = 0.1667), fitness=0.000315121
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352.19 secs, 7187 evals, 7100 steps, improv/step: 0.169 (last = 0.1667), fitness=0.000315121
352.72 secs, 7199 evals, 7112 steps, improv/step: 0.169 (last = 0.0000), fitness=0.000315121
353.24 secs, 7211 evals, 7124 steps, improv/step: 0.169 (last = 0.0833), fitness=0.000315121
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355.35 secs, 7258 evals, 7171 steps, improv/step: 0.168 (last = 0.0833), fitness=0.000315121
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357.43 secs, 7305 evals, 7218 steps, improv/step: 0.168 (last = 0.1818), fitness=0.000315121
357.98 secs, 7317 evals, 7230 steps, improv/step: 0.168 (last = 0.1667), fitness=0.000315121
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360.11 secs, 7365 evals, 7278 steps, improv/step: 0.168 (last = 0.0833), fitness=0.000315121
360.63 secs, 7377 evals, 7290 steps, improv/step: 0.168 (last = 0.1667), fitness=0.000315121
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361.70 secs, 7401 evals, 7315 steps, improv/step: 0.168 (last = 0.1667), fitness=0.000315121
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363.27 secs, 7436 evals, 7350 steps, improv/step: 0.168 (last = 0.1818), fitness=0.000315121
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364.32 secs, 7460 evals, 7374 steps, improv/step: 0.167 (last = 0.0000), fitness=0.000315121
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365.35 secs, 7483 evals, 7397 steps, improv/step: 0.167 (last = 0.0909), fitness=0.000315121
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366.38 secs, 7506 evals, 7420 steps, improv/step: 0.167 (last = 0.1667), fitness=0.000315121
366.93 secs, 7515 evals, 7429 steps, improv/step: 0.167 (last = 0.1111), fitness=0.000315121
367.45 secs, 7523 evals, 7437 steps, improv/step: 0.167 (last = 0.1250), fitness=0.000315121
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372.32 secs, 7587 evals, 7501 steps, improv/step: 0.167 (last = 0.1250), fitness=0.000315121
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375.01 secs, 7617 evals, 7531 steps, improv/step: 0.167 (last = 0.1429), fitness=0.000315121
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376.04 secs, 7635 evals, 7549 steps, improv/step: 0.167 (last = 0.2500), fitness=0.000315121
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378.17 secs, 7674 evals, 7588 steps, improv/step: 0.166 (last = 0.0909), fitness=0.000268346
378.69 secs, 7686 evals, 7600 steps, improv/step: 0.167 (last = 0.3333), fitness=0.000268346
379.21 secs, 7697 evals, 7611 steps, improv/step: 0.166 (last = 0.0000), fitness=0.000268346
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380.25 secs, 7719 evals, 7633 steps, improv/step: 0.166 (last = 0.0909), fitness=0.000268346
380.80 secs, 7731 evals, 7645 steps, improv/step: 0.166 (last = 0.0833), fitness=0.000268346
381.30 secs, 7742 evals, 7656 steps, improv/step: 0.166 (last = 0.4545), fitness=0.000248734
381.80 secs, 7753 evals, 7667 steps, improv/step: 0.166 (last = 0.0000), fitness=0.000248734
382.35 secs, 7765 evals, 7679 steps, improv/step: 0.166 (last = 0.0833), fitness=0.000248734
382.85 secs, 7776 evals, 7690 steps, improv/step: 0.166 (last = 0.0909), fitness=0.000248734
383.38 secs, 7787 evals, 7701 steps, improv/step: 0.166 (last = 0.0909), fitness=0.000248734
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384.40 secs, 7809 evals, 7723 steps, improv/step: 0.166 (last = 0.0909), fitness=0.000248734
384.91 secs, 7820 evals, 7734 steps, improv/step: 0.166 (last = 0.0909), fitness=0.000248734
385.42 secs, 7831 evals, 7745 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000248734
385.94 secs, 7842 evals, 7756 steps, improv/step: 0.165 (last = 0.1818), fitness=0.000248734
386.45 secs, 7852 evals, 7766 steps, improv/step: 0.165 (last = 0.1000), fitness=0.000248734
386.97 secs, 7863 evals, 7777 steps, improv/step: 0.165 (last = 0.2727), fitness=0.000248734
387.51 secs, 7871 evals, 7785 steps, improv/step: 0.165 (last = 0.1250), fitness=0.000248734
388.03 secs, 7880 evals, 7794 steps, improv/step: 0.166 (last = 0.2222), fitness=0.000248734
388.53 secs, 7891 evals, 7805 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000248734
389.04 secs, 7902 evals, 7816 steps, improv/step: 0.165 (last = 0.1818), fitness=0.000248734
389.55 secs, 7913 evals, 7827 steps, improv/step: 0.166 (last = 0.2727), fitness=0.000248734
390.06 secs, 7924 evals, 7838 steps, improv/step: 0.165 (last = 0.0000), fitness=0.000248734
390.57 secs, 7935 evals, 7849 steps, improv/step: 0.165 (last = 0.1818), fitness=0.000248734
391.07 secs, 7946 evals, 7860 steps, improv/step: 0.165 (last = 0.0000), fitness=0.000248734
391.58 secs, 7957 evals, 7871 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000248734
392.12 secs, 7969 evals, 7883 steps, improv/step: 0.165 (last = 0.0000), fitness=0.000248734
392.64 secs, 7981 evals, 7895 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000241049
393.20 secs, 7993 evals, 7907 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000241049
393.72 secs, 8005 evals, 7919 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000241049
394.27 secs, 8017 evals, 7931 steps, improv/step: 0.165 (last = 0.3333), fitness=0.000241049
394.79 secs, 8029 evals, 7943 steps, improv/step: 0.165 (last = 0.3333), fitness=0.000241049
395.34 secs, 8041 evals, 7955 steps, improv/step: 0.165 (last = 0.2500), fitness=0.000241049
395.86 secs, 8053 evals, 7967 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000241049
396.40 secs, 8065 evals, 7979 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000228842
396.91 secs, 8076 evals, 7990 steps, improv/step: 0.165 (last = 0.2727), fitness=0.000228842
397.45 secs, 8088 evals, 8002 steps, improv/step: 0.165 (last = 0.2500), fitness=0.000228842
397.97 secs, 8100 evals, 8014 steps, improv/step: 0.165 (last = 0.0000), fitness=0.000228842
398.53 secs, 8112 evals, 8026 steps, improv/step: 0.165 (last = 0.2500), fitness=0.000110057
399.03 secs, 8123 evals, 8037 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000107167
399.57 secs, 8135 evals, 8049 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
400.07 secs, 8146 evals, 8060 steps, improv/step: 0.165 (last = 0.2727), fitness=0.000107167
400.60 secs, 8158 evals, 8072 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000107167
401.11 secs, 8169 evals, 8083 steps, improv/step: 0.165 (last = 0.0000), fitness=0.000107167
401.61 secs, 8180 evals, 8094 steps, improv/step: 0.165 (last = 0.1818), fitness=0.000107167
402.14 secs, 8192 evals, 8106 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000107167
402.64 secs, 8202 evals, 8116 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000107167
403.15 secs, 8213 evals, 8127 steps, improv/step: 0.164 (last = 0.0909), fitness=0.000107167
403.69 secs, 8225 evals, 8139 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000107167
404.23 secs, 8236 evals, 8150 steps, improv/step: 0.164 (last = 0.0909), fitness=0.000107167
404.73 secs, 8248 evals, 8162 steps, improv/step: 0.164 (last = 0.3333), fitness=0.000107167
405.29 secs, 8260 evals, 8174 steps, improv/step: 0.165 (last = 0.3333), fitness=0.000107167
405.81 secs, 8272 evals, 8186 steps, improv/step: 0.165 (last = 0.2500), fitness=0.000107167
406.35 secs, 8284 evals, 8198 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000107167
406.88 secs, 8295 evals, 8209 steps, improv/step: 0.165 (last = 0.1818), fitness=0.000107167
407.39 secs, 8306 evals, 8220 steps, improv/step: 0.164 (last = 0.0909), fitness=0.000107167
407.91 secs, 8318 evals, 8232 steps, improv/step: 0.165 (last = 0.5000), fitness=0.000107167
408.45 secs, 8330 evals, 8244 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000107167
408.96 secs, 8341 evals, 8255 steps, improv/step: 0.165 (last = 0.3636), fitness=0.000107167
409.49 secs, 8353 evals, 8268 steps, improv/step: 0.165 (last = 0.2308), fitness=0.000107167
410.04 secs, 8365 evals, 8280 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000107167
410.58 secs, 8377 evals, 8292 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
411.09 secs, 8388 evals, 8303 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000107167
411.61 secs, 8400 evals, 8315 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000107167
412.16 secs, 8412 evals, 8327 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
412.69 secs, 8424 evals, 8339 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
413.23 secs, 8436 evals, 8351 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
413.74 secs, 8448 evals, 8363 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
414.25 secs, 8459 evals, 8374 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000107167
414.78 secs, 8471 evals, 8386 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000107167
415.32 secs, 8482 evals, 8397 steps, improv/step: 0.165 (last = 0.0909), fitness=0.000107167
415.83 secs, 8490 evals, 8405 steps, improv/step: 0.165 (last = 0.1250), fitness=0.000107167
416.36 secs, 8502 evals, 8417 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000101449
416.87 secs, 8513 evals, 8428 steps, improv/step: 0.165 (last = 0.1818), fitness=0.000101449
417.41 secs, 8525 evals, 8440 steps, improv/step: 0.165 (last = 0.0833), fitness=0.000101449
417.93 secs, 8537 evals, 8452 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000101449
418.46 secs, 8548 evals, 8463 steps, improv/step: 0.165 (last = 0.3636), fitness=0.000101449
419.01 secs, 8560 evals, 8475 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000101449
419.53 secs, 8572 evals, 8487 steps, improv/step: 0.164 (last = 0.2500), fitness=0.000101449
420.07 secs, 8584 evals, 8499 steps, improv/step: 0.164 (last = 0.0833), fitness=0.000101449
420.57 secs, 8596 evals, 8511 steps, improv/step: 0.164 (last = 0.2500), fitness=0.000101449
421.11 secs, 8608 evals, 8523 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000101449
421.63 secs, 8620 evals, 8535 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000101449
422.17 secs, 8632 evals, 8547 steps, improv/step: 0.164 (last = 0.2500), fitness=0.000101449
422.69 secs, 8644 evals, 8559 steps, improv/step: 0.164 (last = 0.1667), fitness=0.000101449
423.23 secs, 8656 evals, 8571 steps, improv/step: 0.164 (last = 0.1667), fitness=0.000101449
423.74 secs, 8668 evals, 8583 steps, improv/step: 0.164 (last = 0.0833), fitness=0.000101449
424.25 secs, 8679 evals, 8594 steps, improv/step: 0.164 (last = 0.1818), fitness=0.000101449
424.76 secs, 8691 evals, 8606 steps, improv/step: 0.164 (last = 0.1667), fitness=0.000101449
425.30 secs, 8703 evals, 8618 steps, improv/step: 0.164 (last = 0.2500), fitness=0.000101449
425.80 secs, 8715 evals, 8630 steps, improv/step: 0.164 (last = 0.2500), fitness=0.000053724
426.35 secs, 8727 evals, 8642 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000053724
426.86 secs, 8738 evals, 8653 steps, improv/step: 0.164 (last = 0.1818), fitness=0.000053724
427.39 secs, 8748 evals, 8663 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000053724
427.89 secs, 8759 evals, 8674 steps, improv/step: 0.164 (last = 0.1818), fitness=0.000053724
428.42 secs, 8770 evals, 8685 steps, improv/step: 0.164 (last = 0.2727), fitness=0.000053724
428.95 secs, 8782 evals, 8697 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000053724
429.45 secs, 8793 evals, 8708 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000053724
429.96 secs, 8805 evals, 8720 steps, improv/step: 0.164 (last = 0.2500), fitness=0.000053724
430.49 secs, 8817 evals, 8732 steps, improv/step: 0.164 (last = 0.1667), fitness=0.000053724
430.99 secs, 8829 evals, 8744 steps, improv/step: 0.164 (last = 0.0000), fitness=0.000053724
431.53 secs, 8841 evals, 8756 steps, improv/step: 0.163 (last = 0.0833), fitness=0.000053724
432.04 secs, 8852 evals, 8767 steps, improv/step: 0.163 (last = 0.1818), fitness=0.000053724
432.57 secs, 8864 evals, 8779 steps, improv/step: 0.163 (last = 0.0833), fitness=0.000053724
433.08 secs, 8876 evals, 8791 steps, improv/step: 0.163 (last = 0.2500), fitness=0.000053724
433.61 secs, 8888 evals, 8803 steps, improv/step: 0.163 (last = 0.0833), fitness=0.000053724
434.14 secs, 8900 evals, 8815 steps, improv/step: 0.163 (last = 0.0000), fitness=0.000053724
434.67 secs, 8912 evals, 8827 steps, improv/step: 0.163 (last = 0.1667), fitness=0.000053724
435.20 secs, 8924 evals, 8839 steps, improv/step: 0.163 (last = 0.0833), fitness=0.000053724
435.74 secs, 8936 evals, 8851 steps, improv/step: 0.163 (last = 0.0000), fitness=0.000053724
436.25 secs, 8948 evals, 8863 steps, improv/step: 0.163 (last = 0.0000), fitness=0.000053724
436.78 secs, 8960 evals, 8875 steps, improv/step: 0.163 (last = 0.2500), fitness=0.000053724
437.31 secs, 8971 evals, 8886 steps, improv/step: 0.163 (last = 0.2727), fitness=0.000053724
437.83 secs, 8983 evals, 8898 steps, improv/step: 0.163 (last = 0.0833), fitness=0.000053724
438.36 secs, 8995 evals, 8910 steps, improv/step: 0.163 (last = 0.0833), fitness=0.000053724
438.91 secs, 9007 evals, 8922 steps, improv/step: 0.163 (last = 0.1667), fitness=0.000053724
439.41 secs, 9018 evals, 8933 steps, improv/step: 0.162 (last = 0.0000), fitness=0.000053724
439.94 secs, 9030 evals, 8945 steps, improv/step: 0.162 (last = 0.1667), fitness=0.000053724
440.46 secs, 9041 evals, 8956 steps, improv/step: 0.162 (last = 0.0909), fitness=0.000053724
440.97 secs, 9053 evals, 8968 steps, improv/step: 0.162 (last = 0.1667), fitness=0.000053724
441.52 secs, 9065 evals, 8980 steps, improv/step: 0.162 (last = 0.2500), fitness=0.000053724
442.05 secs, 9077 evals, 8992 steps, improv/step: 0.162 (last = 0.1667), fitness=0.000038104
442.59 secs, 9089 evals, 9004 steps, improv/step: 0.162 (last = 0.0000), fitness=0.000038104
443.11 secs, 9101 evals, 9016 steps, improv/step: 0.162 (last = 0.0000), fitness=0.000038104
443.65 secs, 9113 evals, 9028 steps, improv/step: 0.162 (last = 0.0833), fitness=0.000038104
444.16 secs, 9124 evals, 9039 steps, improv/step: 0.162 (last = 0.0000), fitness=0.000038104
444.72 secs, 9136 evals, 9051 steps, improv/step: 0.162 (last = 0.2500), fitness=0.000038104
445.24 secs, 9148 evals, 9063 steps, improv/step: 0.162 (last = 0.0000), fitness=0.000038104
445.78 secs, 9160 evals, 9075 steps, improv/step: 0.162 (last = 0.1667), fitness=0.000038104
446.29 secs, 9172 evals, 9087 steps, improv/step: 0.161 (last = 0.0000), fitness=0.000038104
446.85 secs, 9184 evals, 9099 steps, improv/step: 0.161 (last = 0.0000), fitness=0.000038104
447.36 secs, 9195 evals, 9110 steps, improv/step: 0.161 (last = 0.2727), fitness=0.000038104
447.87 secs, 9205 evals, 9120 steps, improv/step: 0.161 (last = 0.1000), fitness=0.000038104
448.43 secs, 9212 evals, 9127 steps, improv/step: 0.161 (last = 0.4286), fitness=0.000038104
448.93 secs, 9223 evals, 9138 steps, improv/step: 0.161 (last = 0.0909), fitness=0.000038104
449.47 secs, 9235 evals, 9150 steps, improv/step: 0.161 (last = 0.0833), fitness=0.000038104
449.99 secs, 9246 evals, 9161 steps, improv/step: 0.161 (last = 0.0909), fitness=0.000038104
450.51 secs, 9257 evals, 9172 steps, improv/step: 0.161 (last = 0.0909), fitness=0.000038104
451.01 secs, 9269 evals, 9184 steps, improv/step: 0.161 (last = 0.0000), fitness=0.000038104
451.55 secs, 9281 evals, 9196 steps, improv/step: 0.161 (last = 0.0833), fitness=0.000038104
452.06 secs, 9293 evals, 9208 steps, improv/step: 0.161 (last = 0.2500), fitness=0.000038104
452.59 secs, 9305 evals, 9220 steps, improv/step: 0.161 (last = 0.0833), fitness=0.000038104
453.11 secs, 9317 evals, 9232 steps, improv/step: 0.161 (last = 0.3333), fitness=0.000038104
453.62 secs, 9328 evals, 9243 steps, improv/step: 0.161 (last = 0.0909), fitness=0.000038104
454.15 secs, 9340 evals, 9255 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000038104
454.65 secs, 9351 evals, 9266 steps, improv/step: 0.161 (last = 0.1818), fitness=0.000038104
455.16 secs, 9363 evals, 9278 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000038104
455.70 secs, 9375 evals, 9290 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000038104
456.23 secs, 9387 evals, 9302 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000038104
456.76 secs, 9398 evals, 9313 steps, improv/step: 0.161 (last = 0.2727), fitness=0.000038104
457.30 secs, 9408 evals, 9323 steps, improv/step: 0.161 (last = 0.3000), fitness=0.000038104
457.82 secs, 9420 evals, 9335 steps, improv/step: 0.161 (last = 0.0000), fitness=0.000038104
458.36 secs, 9432 evals, 9347 steps, improv/step: 0.161 (last = 0.0000), fitness=0.000038104
458.88 secs, 9444 evals, 9359 steps, improv/step: 0.161 (last = 0.0833), fitness=0.000038104
459.39 secs, 9455 evals, 9370 steps, improv/step: 0.161 (last = 0.0909), fitness=0.000038104
459.91 secs, 9467 evals, 9382 steps, improv/step: 0.161 (last = 0.2500), fitness=0.000038104
460.43 secs, 9479 evals, 9394 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000038104
460.96 secs, 9491 evals, 9406 steps, improv/step: 0.161 (last = 0.0833), fitness=0.000038104
461.47 secs, 9502 evals, 9417 steps, improv/step: 0.161 (last = 0.0000), fitness=0.000038104
462.00 secs, 9514 evals, 9429 steps, improv/step: 0.161 (last = 0.2500), fitness=0.000038104
462.51 secs, 9525 evals, 9440 steps, improv/step: 0.160 (last = 0.0000), fitness=0.000038104
463.05 secs, 9537 evals, 9452 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000038104
463.59 secs, 9549 evals, 9464 steps, improv/step: 0.161 (last = 0.2500), fitness=0.000033359
464.11 secs, 9560 evals, 9475 steps, improv/step: 0.161 (last = 0.2727), fitness=0.000033359
464.61 secs, 9571 evals, 9486 steps, improv/step: 0.161 (last = 0.0909), fitness=0.000033359
465.15 secs, 9583 evals, 9498 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000033359
465.65 secs, 9594 evals, 9509 steps, improv/step: 0.160 (last = 0.0909), fitness=0.000033359
466.17 secs, 9606 evals, 9521 steps, improv/step: 0.161 (last = 0.2500), fitness=0.000033359
466.73 secs, 9618 evals, 9533 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000033359
467.24 secs, 9629 evals, 9544 steps, improv/step: 0.161 (last = 0.1818), fitness=0.000033359
467.76 secs, 9641 evals, 9556 steps, improv/step: 0.161 (last = 0.1667), fitness=0.000033359
468.30 secs, 9653 evals, 9568 steps, improv/step: 0.161 (last = 0.0833), fitness=0.000033359
468.84 secs, 9665 evals, 9580 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000033359
469.34 secs, 9676 evals, 9591 steps, improv/step: 0.160 (last = 0.0000), fitness=0.000033359
469.85 secs, 9688 evals, 9603 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000033359
470.35 secs, 9699 evals, 9614 steps, improv/step: 0.160 (last = 0.0000), fitness=0.000033359
470.87 secs, 9711 evals, 9627 steps, improv/step: 0.160 (last = 0.0769), fitness=0.000033359
471.40 secs, 9723 evals, 9639 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000033359
471.91 secs, 9735 evals, 9651 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000033359
472.46 secs, 9747 evals, 9663 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000033359
472.99 secs, 9759 evals, 9675 steps, improv/step: 0.160 (last = 0.4167), fitness=0.000025629
473.54 secs, 9771 evals, 9687 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000025629
474.08 secs, 9783 evals, 9699 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000025629
474.62 secs, 9795 evals, 9711 steps, improv/step: 0.160 (last = 0.3333), fitness=0.000025629
475.15 secs, 9807 evals, 9723 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000025629
475.65 secs, 9818 evals, 9734 steps, improv/step: 0.160 (last = 0.1818), fitness=0.000025629
476.18 secs, 9830 evals, 9746 steps, improv/step: 0.160 (last = 0.3333), fitness=0.000025629
476.71 secs, 9842 evals, 9758 steps, improv/step: 0.160 (last = 0.2500), fitness=0.000025629
477.24 secs, 9854 evals, 9770 steps, improv/step: 0.160 (last = 0.0000), fitness=0.000025629
477.80 secs, 9866 evals, 9782 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000025629
478.31 secs, 9877 evals, 9793 steps, improv/step: 0.160 (last = 0.1818), fitness=0.000025629
478.83 secs, 9889 evals, 9805 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000025629
479.36 secs, 9900 evals, 9816 steps, improv/step: 0.160 (last = 0.1818), fitness=0.000025629
479.86 secs, 9911 evals, 9827 steps, improv/step: 0.160 (last = 0.0909), fitness=0.000025629
480.37 secs, 9922 evals, 9838 steps, improv/step: 0.160 (last = 0.2727), fitness=0.000025629
480.87 secs, 9933 evals, 9849 steps, improv/step: 0.160 (last = 0.1818), fitness=0.000025629
481.39 secs, 9945 evals, 9861 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000025629
481.93 secs, 9957 evals, 9873 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000025629
482.46 secs, 9969 evals, 9885 steps, improv/step: 0.160 (last = 0.3333), fitness=0.000025629
482.97 secs, 9980 evals, 9896 steps, improv/step: 0.160 (last = 0.0909), fitness=0.000025629
483.51 secs, 9992 evals, 9908 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000025629
484.04 secs, 10004 evals, 9920 steps, improv/step: 0.160 (last = 0.0000), fitness=0.000025629
484.58 secs, 10016 evals, 9932 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000025629
485.09 secs, 10026 evals, 9942 steps, improv/step: 0.160 (last = 0.1000), fitness=0.000025629
485.61 secs, 10038 evals, 9954 steps, improv/step: 0.160 (last = 0.0833), fitness=0.000025629
486.12 secs, 10050 evals, 9966 steps, improv/step: 0.160 (last = 0.1667), fitness=0.000025629
486.64 secs, 10061 evals, 9977 steps, improv/step: 0.160 (last = 0.0909), fitness=0.000023238
487.17 secs, 10072 evals, 9988 steps, improv/step: 0.160 (last = 0.4545), fitness=0.000023238
487.70 secs, 10083 evals, 9999 steps, improv/step: 0.160 (last = 0.0000), fitness=0.000023238

Optimization stopped after 10001 steps and 487.83 seconds
Termination reason: Max number of steps (10000) reached
Steps per second = 20.50
Function evals per second = 20.67
Improvements/step = 0.16010
Total function evaluations = 10085


Best candidate found: [0.399998, 0.906487, 2.00825, 1.99975, 0.147545, 0.200009]

Fitness: 0.000023238







    
Out[10]:





BlackBoxOptim.OptimizationResults("adaptive_de_rand_1_bin_radiuslimited", "Max number of steps (10000) reached", 10001, 1.575471113486e9, 487.8269999027252, DictChain{Symbol,Any}[DictChain{Symbol,Any}[Dict{Symbol,Any}(:RngSeed => 342670,:SearchRange => Tuple{Float64,Float64}[(0.1, 1.0), (0.1, 1.0), (1.5, 4.0), (1.5, 4.0), (0.05, 0.2), (0.1, 0.25)],:MaxSteps => 10000),Dict{Symbol,Any}()],Dict{Symbol,Any}(:FitnessScheme => ScalarFitnessScheme{true}(),:NumDimensions => :NotSpecified,:PopulationSize => 50,:MaxTime => 0.0,:SearchRange => (-1.0, 1.0),:Method => :adaptive_de_rand_1_bin_radiuslimited,:MaxNumStepsWithoutFuncEvals => 100,:RngSeed => 1234,:MaxFuncEvals => 0,:SaveTrace => false…)], 10085, ScalarFitnessScheme{true}(), BlackBoxOptim.TopListArchiveOutput{Float64,Array{Float64,1}}(2.3238332610212827e-5, [0.39999813542572393, 0.9064870289371078, 2.00825093694817, 1.9997457371433491, 0.1475451964727831, 0.2000090042657465]), BlackBoxOptim.PopulationOptimizerOutput{FitPopulation{Float64}}(FitPopulation{Float64}([0.39999582023968416 0.40001800302277785 … 0.40001221274438725 0.40001800864570025; 0.9078550844700933 0.9091649276507853 … 0.9114258086692654 0.9095210926662284; … ; 0.14715018424724421 0.14654537262428868 … 0.14584056186934855 0.1463809761718443; 0.19999804049034417 0.19995705152087756 … 0.199963412237228 0.19994596155104924], NaN, [5.315979445569093e-5, 8.764278374106651e-5, 8.832596520856464e-5, 6.901331317996151e-5, 8.242978158802385e-5, 7.70125950469246e-5, 8.15601464586419e-5, 6.598260803961049e-5, 7.628067381300808e-5, 9.448251633839513e-5  …  5.673979268488549e-5, 7.22925623979078e-5, 9.544172868589259e-5, 7.026649046163648e-5, 5.9152649497055956e-5, 5.372443810614412e-5, 5.30295787749722e-5, 0.00010297374370435685, 0.00010501626560904943, 0.00011227855411683369], 0, BlackBoxOptim.Candidate{Float64}[BlackBoxOptim.Candidate{Float64}([0.40001666207095155, 0.9045613269369748, 2.005576804298473, 2.0000691400643276, 0.14831257133000528, 0.1999930266209056], 33, 4.1716694147443185e-5, BlackBoxOptim.AdaptiveDiffEvoRandBin{3}(BlackBoxOptim.AdaptiveDiffEvoParameters(BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.65, σ=0.1), Distributions.Cauchy{Float64}(μ=1.0, σ=0.1), 0.5, false, true), BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.1, σ=0.1), Distributions.Cauchy{Float64}(μ=0.95, σ=0.1), 0.5, false, true), [0.960674322251959, 0.9581303909794152, 0.8522871247779139, 0.7610893640593427, 0.659582004449304, 0.48178863349694556, 0.6950846231523309, 0.8704360788207649, 0.9219643404375019, 1.0  …  1.0, 0.9386474095440099, 0.9543424300003557, 0.43907300833940044, 0.6394905172733162, 1.0, 1.0, 0.5199196870001682, 0.9649232696695624, 0.9123915541318597], [1.0, 1.0, 0.8522356164335076, 1.0, 1.0, 0.7120976372546113, 0.12389854064189035, 1.0, 0.17941474174929367, 0.9853649515873368  …  0.6567290434385484, 0.023304418985069034, 0.9341063811312418, 0.7962778660507044, 1.0, 1.0, 0.0138724141191999, 0.774083152274134, 0.07115539976214924, 1.0])), 0), BlackBoxOptim.Candidate{Float64}([0.4000163051337856, 0.9045613269369748, 2.005231804867753, 2.0000691400643276, 0.14831257133000528, 0.20000265157474725], 33, 7.56482239289737e-5, BlackBoxOptim.AdaptiveDiffEvoRandBin{3}(BlackBoxOptim.AdaptiveDiffEvoParameters(BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.65, σ=0.1), Distributions.Cauchy{Float64}(μ=1.0, σ=0.1), 0.5, false, true), BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.1, σ=0.1), Distributions.Cauchy{Float64}(μ=0.95, σ=0.1), 0.5, false, true), [0.960674322251959, 0.9581303909794152, 0.8522871247779139, 0.7610893640593427, 0.659582004449304, 0.48178863349694556, 0.6950846231523309, 0.8704360788207649, 0.9219643404375019, 1.0  …  1.0, 0.9386474095440099, 0.9543424300003557, 0.43907300833940044, 0.6394905172733162, 1.0, 1.0, 0.5199196870001682, 0.9649232696695624, 0.9123915541318597], [1.0, 1.0, 0.8522356164335076, 1.0, 1.0, 0.7120976372546113, 0.12389854064189035, 1.0, 0.17941474174929367, 0.9853649515873368  …  0.6567290434385484, 0.023304418985069034, 0.9341063811312418, 0.7962778660507044, 1.0, 1.0, 0.0138724141191999, 0.774083152274134, 0.07115539976214924, 1.0])), 0)])))

In [11]:

    

best_candidate(res)


    

    
Out[11]:





6-element Array{Float64,1}:
 0.39999813542572393
 0.9064870289371078 
 2.00825093694817   
 1.9997457371433491 
 0.1475451964727831 
 0.2000090042657465 

In [12]:

    

x_init = best_candidate(res)
vis_error(x_init, exp_data1, core_props, fluids, core_flood)
error_calc(x_init, exp_data1, core_props, fluids, core_flood)


    

    













    













    
Out[12]:





1.1439755442283902e-5

In [14]:

    

using JuMP, Ipopt


    

In [33]:

    

# weight factors:
w_p = ones(length(exp_data1.dp_exp))
temp_val, ind_max = findmax(exp_data1.dp_exp)
# println(ind_max)
w_p[ind_max-1:ind_max+1] .= 10
w_p[end-10:end] .= 1
w_p[1]=1
w_R = ones(length(exp_data1.R_exp))
w_R[20:25] .= 1
w_R[end-10:end] .= 10

# [krw0, kro0, nw, no, swc, sor]

function my_f(krw0, kro0, nw, no, swc, sor)
    f_val = error_calc([krw0, kro0, nw, no, swc, sor], exp_data1, core_props, 
            fluids, core_flood, w_p = w_p, w_R = w_R)
    return f_val
end

function ∇f(g_val, krw0, kro0, nw, no, swc, sor)
    eps1 = 1e-4
    x = [krw0, kro0, nw, no, swc, sor]
    f_val = my_f(krw0, kro0, nw, no, swc, sor)
    g_val = zeros(length(x))
    for j in eachindex(x)
        x2 = copy(x)
        x2[j]+=eps1
        f_val2 = my_f(x2...)
        g_val[j] = (f_val2-f_val)/eps1
    end
    return g_val
end

# test
grad_x = zeros(6)
my_f(1.0, 0.8, 3, 4, 0.2, 0.2)

# ∇f(1.0, 0.8, 2, 2, 0.1, 0.2)


    

    
Out[33]:





0.4548076217562965

In [34]:

    

model = Model(with_optimizer(Ipopt.Optimizer))
# [krw0, kro0, nw, no, swc, sor]
@variable(model, 0.1 <= kro0 <= 1.0, start = x_init[2])
@variable(model, 0.1 <= krw0 <= 1.0, start = x_init[1])
@variable(model, 0.01 <= sor <= 0.4, start = x_init[6])
@variable(model, 0.01 <= swc <= 0.4, start = x_init[5])
@variable(model, 1.0 <= no <= 4.0, start = x_init[4])
@variable(model, 1.0 <= nw <= 4.0, start = x_init[3])

register(model, :my_f, 6, my_f, ∇f)

@NLobjective(model, Min, my_f(krw0, kro0, nw, no, swc, sor))

# JuMP.register(model::Model, s::Symbol, dimension::Integer, f::Function,
#               ∇f::Function, ∇²f::Function)
# my_f(x, y) = (x - 1)^2 + (y - 2)^2
# function ∇f(g, x, y)
#     g[1] = 2 * (x - 1)
#     g[2] = 2 * (y - 2)
# end
JuMP.optimize!(model)


    

    




This is Ipopt version 3.12.10, running with linear solver mumps.
NOTE: Other linear solvers might be more efficient (see Ipopt documentation).

Number of nonzeros in equality constraint Jacobian...:        0
Number of nonzeros in inequality constraint Jacobian.:        0
Number of nonzeros in Lagrangian Hessian.............:        0

Total number of variables............................:        6
                     variables with only lower bounds:        0
                variables with lower and upper bounds:        6
                     variables with only upper bounds:        0
Total number of equality constraints.................:        0
Total number of inequality constraints...............:        0
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:        0

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
   0  9.3697354e-03 0.00e+00 0.00e+00   0.0 0.00e+00    -  0.00e+00 0.00e+00   0
   1  9.3696120e-03 0.00e+00 6.09e-07  -6.1 6.15e-07    -  9.90e-01 1.00e+00f  1
   2  1.1392894e-02 0.00e+00 9.54e-02  -2.2 9.54e-02    -  1.00e+00 2.50e-01f  3
   3  1.1392894e-02 0.00e+00 3.01e-02  -2.2 3.01e-02    -  1.00e+00 1.42e-14f 47
   4  1.1392894e-02 0.00e+00 3.67e-03  -3.4 3.67e-03    -  1.00e+00 5.68e-14f 45
   5  1.1392894e-02 0.00e+00 1.11e-04  -5.0 1.11e-04    -  1.00e+00 9.09e-13f 41
   6  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 9.09e-13f 41
   7  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
   8  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
   9  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  10  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  11  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  12  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  13  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  14  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  15  1.1408078e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  16  1.1423256e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  17  1.1438428e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  18  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 42
  19  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  20  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  21  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  22  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  23  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  24  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  25  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  26  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  27  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  28  1.1408078e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  29  1.1423256e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  30  1.1438428e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  31  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 42
  32  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  33  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  34  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  35  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  36  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  37  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  38  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  39  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  40  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  41  1.1408078e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  42  1.1423256e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  43  1.1438428e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  44  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 42
  45  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  46  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  47  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  48  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  49  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  50  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  51  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  52  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  53  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  54  1.1408078e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  55  1.1423256e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  56  1.1438428e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 1.00e+00w  1
  57  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 42
  58  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  59  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  60  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  61  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43
  62  1.1392894e-02 0.00e+00 1.17e-04  -5.0 1.17e-04    -  1.00e+00 2.27e-13f 43






    




InterruptException:

Stacktrace:
 [1] (::getfield(Main.FractionalFlow, Symbol("##45#49")){Float64,Float64,Float64,Float64})(::Float64) at /home/ali/projects/peteng/analytical/FractionalFlow/FractionalFlow.jl:357
 [2] _broadcast_getindex_evalf at ./broadcast.jl:625 [inlined]
 [3] _broadcast_getindex at ./broadcast.jl:598 [inlined]
 [4] getindex at ./broadcast.jl:558 [inlined]
 [5] copyto_nonleaf!(::Array{Float64,1}, ::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1},Tuple{Base.OneTo{Int64}},getfield(Main.FractionalFlow, Symbol("##45#49")){Float64,Float64,Float64,Float64},Tuple{Base.Broadcast.Extruded{Array{Float64,1},Tuple{Bool},Tuple{Int64}}}}, ::Base.OneTo{Int64}, ::Int64, ::Int64) at ./broadcast.jl:982
 [6] copy(::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1},Tuple{Base.OneTo{Int64}},getfield(Main.FractionalFlow, Symbol("##45#49")){Float64,Float64,Float64,Float64},Tuple{Array{Float64,1}}}) at ./broadcast.jl:836
 [7] materialize at ./broadcast.jl:798 [inlined]
 [8] water_flood(::Main.FractionalFlow.CoreProperties, ::Main.FractionalFlow.Fluids, ::Main.FractionalFlow.CoreyRelativePermeability, ::Main.FractionalFlow.CoreFlooding) at /home/ali/projects/peteng/analytical/FractionalFlow/water_flood.jl:86
 [9] #error_calc#3(::Array{Float64,1}, ::Array{Float64,1}, ::typeof(error_calc), ::Array{Float64,1}, ::exp_data, ::Main.FractionalFlow.CoreProperties, ::Main.FractionalFlow.Fluids, ::Main.FractionalFlow.CoreFlooding) at ./In[7]:7
 [10] (::getfield(Main, Symbol("#kw##error_calc")))(::NamedTuple{(:w_p, :w_R),Tuple{Array{Float64,1},Array{Float64,1}}}, ::typeof(error_calc), ::Array{Float64,1}, ::exp_data, ::Main.FractionalFlow.CoreProperties, ::Main.FractionalFlow.Fluids, ::Main.FractionalFlow.CoreFlooding) at ./none:0
 [11] my_f(::Float64, ::Float64, ::Float64, ::Float64, ::Float64, ::Float64) at ./In[33]:15
 [12] ∇f(::SubArray{Float64,1,Array{Float64,1},Tuple{UnitRange{Int64}},true}, ::Float64, ::Float64, ::Float64, ::Float64, ::Float64, ::Float64) at ./In[33]:28
 [13] (::getfield(JuMP, Symbol("##97#100")){typeof(∇f)})(::SubArray{Float64,1,Array{Float64,1},Tuple{UnitRange{Int64}},true}, ::SubArray{Float64,1,Array{Float64,1},Tuple{UnitRange{Int64}},true}) at /home/ali/.julia/packages/JuMP/MsUSY/src/nlp.jl:1177
 [14] eval_objective_gradient(::JuMP._UserFunctionEvaluator, ::SubArray{Float64,1,Array{Float64,1},Tuple{UnitRange{Int64}},true}, ::SubArray{Float64,1,Array{Float64,1},Tuple{UnitRange{Int64}},true}) at /home/ali/.julia/packages/JuMP/MsUSY/src/nlp.jl:1140
 [15] forward_eval(::Array{Float64,1}, ::Array{Float64,1}, ::Array{JuMP._Derivatives.NodeData,1}, ::SparseArrays.SparseMatrixCSC{Bool,Int64}, ::Array{Float64,1}, ::Array{Float64,1}, ::Array{Float64,1}, ::Array{Float64,1}, ::Array{Float64,1}, ::Array{Float64,1}, ::JuMP._Derivatives.UserOperatorRegistry) at /home/ali/.julia/packages/JuMP/MsUSY/src/_Derivatives/forward.jl:165
 [16] _forward_eval_all(::NLPEvaluator, ::Array{Float64,1}) at /home/ali/.julia/packages/JuMP/MsUSY/src/nlp.jl:503
 [17] macro expansion at /home/ali/.julia/packages/JuMP/MsUSY/src/nlp.jl:536 [inlined]
 [18] macro expansion at ./util.jl:213 [inlined]
 [19] eval_objective(::NLPEvaluator, ::Array{Float64,1}) at /home/ali/.julia/packages/JuMP/MsUSY/src/nlp.jl:534
 [20] eval_objective(::Ipopt.Optimizer, ::Array{Float64,1}) at /home/ali/.julia/packages/Ipopt/ruIXY/src/MOI_wrapper.jl:577
 [21] (::getfield(Ipopt, Symbol("#eval_f_cb#27")){Ipopt.Optimizer})(::Array{Float64,1}) at /home/ali/.julia/packages/Ipopt/ruIXY/src/MOI_wrapper.jl:810
 [22] eval_f_wrapper(::Int32, ::Ptr{Float64}, ::Int32, ::Ptr{Float64}, ::Ptr{Nothing}) at /home/ali/.julia/packages/Ipopt/ruIXY/src/Ipopt.jl:124
 [23] solveProblem(::IpoptProblem) at /home/ali/.julia/packages/Ipopt/ruIXY/src/Ipopt.jl:342
 [24] optimize!(::Ipopt.Optimizer) at /home/ali/.julia/packages/Ipopt/ruIXY/src/MOI_wrapper.jl:914
 [25] optimize!(::MathOptInterface.Bridges.LazyBridgeOptimizer{Ipopt.Optimizer}) at /home/ali/.julia/packages/MathOptInterface/A2UPd/src/Bridges/bridge_optimizer.jl:225
 [26] optimize!(::MathOptInterface.Utilities.CachingOptimizer{MathOptInterface.AbstractOptimizer,MathOptInterface.Utilities.UniversalFallback{MathOptInterface.Utilities.Model{Float64}}}) at /home/ali/.julia/packages/MathOptInterface/A2UPd/src/Utilities/cachingoptimizer.jl:189
 [27] #optimize!#78(::Bool, ::Bool, ::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}, ::typeof(JuMP.optimize!), ::Model, ::Nothing) at /home/ali/.julia/packages/JuMP/MsUSY/src/optimizer_interface.jl:141
 [28] optimize! at /home/ali/.julia/packages/JuMP/MsUSY/src/optimizer_interface.jl:111 [inlined] (repeats 2 times)
 [29] top-level scope at In[34]:13

In [28]:

    

x_init = [value(krw0), value(kro0), value(nw), value(no), value(swc), value(sor)]
vis_error(x_init, exp_data1, core_props, fluids, core_flood)
error_calc(x_init, exp_data1, core_props, fluids, core_flood)


    

    













    













    
Out[28]:





0.007544830494364934

In [18]:

    

x_init


    

    
Out[18]:





6-element Array{Float64,1}:
 0.4412043349923931 
 0.9909989358955247 
 1.5007970424128223 
 2.902481118436997  
 0.13592685333937712
 0.14648578223980793