- class ISRES(max_evals=1000)¶
Improved Stochastic Ranking Evolution Strategy optimizer.
Improved Stochastic Ranking Evolution Strategy (ISRES) is an algorithm for non-linearly constrained global optimization. It has heuristics to escape local optima, even though convergence to a global optima is not guaranteed. The evolution strategy is based on a combination of a mutation rule and differential variation. The fitness ranking is simply via the objective function for problems without nonlinear constraints. When nonlinear constraints are included, the stochastic ranking proposed by Runarsson and Yao is employed. This method supports arbitrary nonlinear inequality and equality constraints, in addition to the bound constraints.
NLopt global optimizer, derivative-free. For further detail, please refer to http://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/#isres-improved-stochastic-ranking-evolution-strategy
int) – Maximum allowed number of function evaluations.
MissingOptionalLibraryError – NLopt library not installed.
Return NLopt optimizer type
return support level dictionary
We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.
Minimize the scalar function.
Print algorithm-specific options.
Set max evals grouped
Sets or updates values in the options dictionary.
Wrap the function to implicitly inject the args at the call of the function.
Returns bounds support level
Returns gradient support level
Returns initial point support level
Returns is bounds ignored
Returns is bounds required
Returns is bounds supported
Returns is gradient ignored
Returns is gradient required
Returns is gradient supported
Returns is initial point ignored
Returns is initial point required
Returns is initial point supported