【优化分配】基于粒子群算法求解火车票分配优化问题含Matlab源码.zip

clc,clear,close all warning off format longG tic; global Nseat Dab Dbc Dac fab fbc fac ti ta tb % 加载参数 parameters; % 系统的参数 % 第index_t期 index_t = 10; Vt_last = 0; % PSO 参数 c1 = 1.4995; c2 = 1.4995; Vmin = -1; Vmax = 1; maxiter = 30; % 迭代次数 sizepop = 50; % 种群数量 nvar = 3; % 3个变量 popmin = 0; popmax = max([ta(index_t),tb(index_t)]); % x % 初始化种群 for i=1:sizepop pop(i,:) = popmin + (popmax-popmin).*rand(1,nvar); fitness(i) = fun(pop(i,:), Vt_last, index_t); V(i,1:3) = 0; end % 记录一组最优值 [bestfitness,bestindex]=min(fitness); zbest=pop(bestindex,:); % 全局最佳 gbest=pop; % 个体最佳 fitnessgbest=fitness; % 个体最佳适应度值 fitnesszbest=bestfitness; % 全局最佳适应度值 wmax = 0.9; wmin = 0.4; % 迭代寻优 for i=1:maxiter for j=1:sizepop % 自适应权重1 % w = wmin + (wmax-wmin)*(fitnessgbest(j)-min(fitness))/( max(fitness)-min(fitness) ); % 自适应权重2 % w = wmin - (wmax-wmin)*(fitnessgbest(j)-min(fitness))/( mean(fitness)-min(fitness) ); % 自适应权重3 if fitnessgbest(j)<=mean(fitness) w = wmin - (wmax-wmin)*(fitnessgbest(j)-min(fitness))/( mean(fitness)-min(fitness) ); else w = wmax; end % 速度更新 V(j,:) = w*V(j,:) + c1*rand*(gbest(j,:) - pop(j,:)) + c2*rand*(zbest - pop(j,:)); % V--防止越界 for k=1:nvar if V(j,k)>Vmax V(j,k)=Vmax; end if V(j,k)<Vmin V(j,k)=Vmin; end end % 个体更新 pop(j,:) = pop(j,:) + 0.5 * V(j,:); % x 越界限制 for k=1:nvar if pop(j,k)>popmax pop(j,k)=popmax; end if pop(j,k)<popmin pop(j,k)=popmin; end end % 适应度更新 fitness(j) = fun(pop(j,:), Vt_last, index_t); % 比较 个体间比较 if fitness(j)<fitnessgbest(j) fitnessgbest(j) = fitness(j); gbest(j,:) = pop(j,:); end if fitness(j)<bestfitness bestfitness = fitness(j); zbest = pop(j,:); end end fitness_iter(i) = bestfitness; end toc ; times = toc; fprintf('\n') disp(['计算时间 Time = ', num2str(times) ]) fprintf('\n') disp(['最优解 ', num2str(zbest)]) fprintf('\n') figure('color',[1,1,1]) plot(fitness_iter,'ro-','linewidth',2) xlabel('迭代次数') ylabel('fitness_iter')