黑寡妇优化算法（BWO）是一种基于黑寡妇蜘蛛交配行为的受自然启发的元启发式优化算法matlab代码.zip

function [best_solution, best_fitness] = black_widow_optimizer(obj_func, num_variables, num_agents, max_iter, lb, ub) % Initialize population population = bsxfun(@plus, lb, bsxfun(@times, rand(num_agents, num_variables), (ub - lb))); fitness = zeros(1, num_agents); % Evaluate fitness of each agent for i = 1:num_agents fitness(i) = obj_func(population(i, :)); end % Main loop for iter = 1:max_iter % Update position and fitness of each agent for i = 1:num_agents % Choose a partner (spider) randomly partner_index = randi(num_agents); while partner_index == i partner_index = randi(num_agents); end % Update position using crossover with the partner new_solution = population(i, :) + rand(1, num_variables) .* (population(partner_index, :) - population(i, :)); % Apply mutation mutation_prob = rand(1, num_variables); mutation_mask = mutation_prob < 0.1; % Mutation rate of 10% new_solution(mutation_mask) = rand(1, sum(mutation_mask)) .* (ub(mutation_mask) - lb(mutation_mask)) + lb(mutation_mask); % Randomly generate new values for mutated genes % Clip new solution to ensure it stays within bounds new_solution = max(min(new_solution, ub), lb); % Evaluate fitness of the new solution new_fitness = obj_func(new_solution); % Update if the new solution is better if new_fitness < fitness(i) population(i, :) = new_solution; fitness(i) = new_fitness; end end end % Find the best solution in the final population [best_fitness, best_index] = min(fitness); best_solution = population(best_index, :); end