摘要
针对作业车间调度问题JSP(Job-shop scheduling problem),提出一种入侵式杂草优化算法。该算法中,子代以正态分布方式在父代个体周围扩散,兼顾全局搜索和局部搜索,并根据迭代次数不同对二者强度进行调节。通过典型算例进行仿真试验,并在反复实验中对算法参数进行修正。测试结果表明杂草算法求解作业车间调度问题的可行性和有效性,优于萤火虫算法和基本粒子群算法,是解决生产调度问题的一种有效方法。
This paper introduces an invasive weed optimisation algorithm aimed at solving job shop scheduling problem.In this algorithm, the offspring diffuses around the parent individuals in the way of normal distribution,combining the global search and local search and adjusting different strength of both according to the number of iterations.Simulation tests are carried out through typical examples,and in repeated experiments the parameters of the algorithm are corrected.Test results demonstrate the feasibility and effectiveness of IWO in solving job shop scheduling problem,it is superior to the firefly algorithm and basic particle swarm optimisation,and is an effective approach for solving production scheduling problem.
作者
黄霞
叶春明
包晓晓
Huang Xia;Bao Xiaoxiao;Ye Chunming(School of Business, University of Shanghai for Science and Technology, Shanghai 200093 , China;Jiangsu University of Science and Technology ,Zhangjiagang 215600, Jiangsu, China)
出处
《计算机应用与软件》
CSCD
2016年第6期231-234,共4页
Computer Applications and Software
基金
国家自然科学基金项目(71271138)
上海市一流学科建设项目(S1201YLXK)
沪江基金项目(A14006)
上海理工大学人文社科攀登计划项目(14XPB01)
关键词
杂草优化算法
作业车间调度问题
最大完工时间
Invasive weed optimisation(IWO) algorithm
Job shop scheduling problem
Makespan
