metaheuristic_designer.strategies.classic

Classic population-based strategies (GA, DE, ES, CMA-ES, SA, RandomSearch).

Modules

CMA_ES(initializer[, survivor_sel, name, ...])	Covariance Matrix Adaptation Evolution Strategy (CMA-ES).
DE(initializer[, de_operator_name, ...])	Differential Evolution algorithm.
ES(initializer, mutation_op[, crossover_op, ...])	Evolution Strategy (μ+λ or μ,λ).
GA(initializer, mutation_op, crossover_op, ...)	Genetic Algorithm.
SA(initializer, operator[, name, ...])	Simulated Annealing algorithm.
hill_climb	Hill Climbing strategy (single-solution, greedy local improvement).
local_search	Local Search strategy (single solution, multiple perturbations per iteration).
random_search	Random search strategy (baseline).