pyanno4rt.optimization.solvers.configurations._configure_pypop7

PyPop7 algorithm configuration.

Overview

Function

configure_pypop7(number_of_variables, problem_instance, lower_variable_bounds, upper_variable_bounds, lower_constraint_bounds, upper_constraint_bounds, algorithm, max_iter, tolerance)

Configure the PyPop7 solver.

Functions

pyanno4rt.optimization.solvers.configurations._configure_pypop7.configure_pypop7(number_of_variables, problem_instance, lower_variable_bounds, upper_variable_bounds, lower_constraint_bounds, upper_constraint_bounds, algorithm, max_iter, tolerance)[source]

Configure the PyPop7 solver.

Supported algorithms: LMCMA, LMMAES.

Parameters:

  • problem_instance (object of class LexicographicOptimization WeightedSumOptimization) – The object representing the optimization problem.

  • lower_variable_bounds (list) – Lower bounds on the decision variables.

  • upper_variable_bounds (list) – Upper bounds on the decision variables.

  • lower_constraint_bounds (list) – Lower bounds on the constraints.

  • upper_constraint_bounds (list) – Upper bounds on the constraints.

  • algorithm (str) – Label for the solution algorithm.

  • initial_fluence (ndarray) – Initial fluence vector.

  • max_iter (int) – Maximum number of iterations.

  • tolerance (float) – Precision goal for the objective function value.

Returns:

  • fun (object) – The object representing the optimization algorithm.

  • arguments (dict) – Dictionary with the function arguments.