Optimization, Programming, Python, Evolutionary Algorithms, Editors Pick.
quite confusing, and gradient-based search directions are definitely leading us nowhere. Let us try and solve the problem to see. sol_cvx_2 = minimize(obj_fun_2, [2.5, 0.0], method="BFGS") sol_de_2 = differential_evolution( obj_fun_2, bounds=[(-5., 5.), (-5., 5.)], popsize=50, strategy="rand1bin",