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I am trying to find the global minimization of the eggholder function:
import nlopt import numpy as np def eggholder(x, grad): return (-(x[1] + 47) * np.sin(np.sqrt(abs(x[0]/2 + (x[1] + 47)))) -x[0] * np.sin(np.sqrt(abs(x[0] - (x[1] + 47))))) x0 = np.zeros(2) opt = nlopt.opt(nlopt.GD_STOGO, x0.size) opt.set_min_objective(eggholder) opt.set_lower_bounds(-512) opt.set_upper_bounds(512) opt.set_xtol_rel(1e-8) %time opt_x = opt.optimize(x0) opt_value = opt.last_optimum_value() opt_result = opt.last_optimize_result()
However, the optimization function keeps running and never finds the global minimum. Does anyone know why the optimize function keeps running?
The text was updated successfully, but these errors were encountered:
maybe it does not converge, try "opt.set_maxeval(1000)" or set_maxtime
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I am trying to find the global minimization of the eggholder function:
However, the optimization function keeps running and never finds the global minimum. Does anyone know why the optimize function keeps running?
The text was updated successfully, but these errors were encountered: