【车间调度】基于GA/PSO/SA/ACO/TS优化算法的车间调度比较（Matlab代码实现）

目录

1 概述

2 运行结果

2.1 标题2.1

2.2 main1运行结果

2.2 main2运行结果

3 Matlab代码

‍4 参考文献

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电气代码	智能算法及其应用
路径规划	神经网络预测
优化调度	图像处理
车间调度	信号处理
浪漫的她	我的哲思
数学建模	完整代码事宜

1 概述

柔性作业车间调度问题(Flexible Job shop Sched-uling Problem , FJSP)是在离散制造业和流程工业中应用广泛的一类问题,已被证明是典型的 NP-上hard问题。

FJSP是作业车间调度问题(Job shop Scheduling Prob-lem,JSP)的扩展,FJSP中每个工件的每道工序均可以在可选择的有限台机器上加工,且在每台机器上的加工时间不一定相同,可灵活地进行资源选择,提高调度的敏捷性,更加贴近实际生产。目前元启发式算法是解决FJSP的常用方法,其主要可分为群体智能算法和局部搜索算法。陆家辉等人提出一种混合。

Jaya优化算法求解柔性作业车间调度问题,并设计一种离散化更新算子使Jaya 优化算法更适用于FJSP,混合2种新型邻域结构提高算法的同守儿→军等人[2将化学反应算法与禁忌搜索相结合,设计了4种操作来保证种群多样性,以实现最优的全局探索,加人禁忌搜索提高了混合算法的局部寻优能力。

详细讲解：车间调度专栏

2 运行结果

2.1 标题2.1

本文包括五种优化算法进行比较，分别是：遗传算法、粒子群优化算法、模拟退火算法、蚂蚁算法、禁忌搜索算法

2.2 main1运行结果

下面看看运行结果比较：

2.2 main2运行结果

3 Matlab代码

function [costs, bestSol] = PSO(jobs, m, n, particals, iterations, costFunc)  c1 = 1.4944;  c2 = 1.4944;  w = 0.79;  gbests = ones(1, n);  gbest = costFunc(gbests, jobs, m, n);  lbests = randi(m, particals, n);  lbest = ones(1, particals);  costs = ones(iterations, 1);  costsEnd = 0;  for i = 1:particals      lbest(i) = costFunc(lbests(i, :), jobs, m, n);      if lbest(i) < gbest          gbest = lbest(i);          gbests = lbests(i, :);      end  end  x = lbests;  v = zeros(particals, n);    for i = 1:iterations      ibest = costFunc(ones(particals, n), jobs, m, n);      r1 = rand(particals, 1);      r2 = rand(particals, 1);      v = w*v + c1 * bsxfun(@times, r1, lbests - x) + ...        c2 * bsxfun(@times, r2, (bsxfun(@minus, gbests, x)));      x = round(x + v);      %x = bsxfun(@mod, x, m) + 1;      x(x < 1) = 1;      x(x > m) = m;      for j = 1:particals          c = costFunc(x(j, :), jobs, m, n);          if c < ibest              ibest = c;          end          if c < lbest(j)              lbest(j) = c;              lbests(j, :) = x(j, :);          end      end      costsEnd = costsEnd + 1;      costs(costsEnd) = ibest;      [ilbest, idx] = min(lbest);      %ibest      ilbests = lbests(idx, :);      if ilbest < gbest          gbest = ilbest;          gbests = ilbests;      end  end  bestSol = gbests;end

function [costs, bestSol] = PSO(jobs, m, n, particals, iterations, costFunc) c1 = 1.4944; c2 = 1.4944; w = 0.79; gbests = ones(1, n); gbest = costFunc(gbests, jobs, m, n); lbests = randi(m, particals, n); lbest = ones(1, particals); costs = ones(iterations, 1); costsEnd = 0; for i = 1:particals lbest(i) = costFunc(lbests(i, :), jobs, m, n); if lbest(i) < gbest gbest = lbest(i); gbests = lbests(i, :); end end x = lbests; v = zeros(particals, n);

完整代码：基于GA/PSO/SA/ACO/TS优化算法的车间调度比较

function [costs, bestSol] = PSO(jobs, m, n, particals, iterations, costFunc) c1 = 1.4944; c2 = 1.4944; w = 0.79; gbests = ones(1, n); gbest = costFunc(gbests, jobs, m, n); lbests = randi(m, particals, n); lbest = ones(1, particals); costs = ones(iterations, 1); costsEnd = 0; for i = 1:particals lbest(i) = costFunc(lbests(i, :), jobs, m, n); if lbest(i) < gbest gbest = lbest(i); gbests = lbests(i, :); end end x = lbests; v = zeros(particals, n);

function [costs, bestSol] = PSO(jobs, m, n, particals, iterations, costFunc) c1 = 1.4944; c2 = 1.4944; w = 0.79; gbests = ones(1, n); gbest = costFunc(gbests, jobs, m, n); lbests = randi(m, particals, n); lbest = ones(1, particals); costs = ones(iterations, 1); costsEnd = 0; for i = 1:particals lbest(i) = costFunc(lbests(i, :), jobs, m, n); if lbest(i) < gbest gbest = lbest(i); gbests = lbests(i, :); end end x = lbests; v = zeros(particals, n);

function [costs, bestSol] = PSO(jobs, m, n, particals, iterations, costFunc) c1 = 1.4944; c2 = 1.4944; w = 0.79; gbests = ones(1, n); gbest = costFunc(gbests, jobs, m, n); lbests = randi(m, particals, n); lbest = ones(1, particals); costs = ones(iterations, 1); costsEnd = 0; for i = 1:particals lbest(i) = costFunc(lbests(i, :), jobs, m, n); if lbest(i) < gbest gbest = lbest(i); gbests = lbests(i, :); end end x = lbests; v = zeros(particals, n);

‍4 参考文献

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[1]王玉芳,曾亚志,蒋亚飞.基于自适应灰狼优化算法的柔性作业车间调度问题[J].现代制造工程,2022(7):1-10

[2]张守京,杜昊天,侯天天.求解多目标双资源柔性车间调度问题的改进NSGA-Ⅱ算法[J].机械科学与技术,2022,41(5):771-778

[3]黄学文,陈绍芬,周阗玉,孙宇婷.求解柔性作业车间调度的遗传算法综述[J].计算机集成制造系统,2022,28(2):536-551

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