基于改进粒子群算法求解分布式多工厂生产调度问题  

Improved Particle Swarm Optimization Algorithm for Distributed Multi-plants Production Scheduling

作　　者：王仕存 唐敦兵[1] 朱海华[1] 聂庆炜 潘俊峰 杨雷 WANG Shicun;TANG Dunbing;ZHU Haihua;NIE Qingwei;PAN Junfeng;YANG Lei(College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Jiangsu Tianan Smart Science&Technology Co.,Ltd.,Wuxi 214171,China)

机构地区：[1]南京航空航天大学机电学院,江苏南京210016 [2]江苏天安智联科技股份有限公司,江苏无锡214171

出　　处：《机械制造与自动化》2021年第4期9-13,共5页Machine Building & Automation

基　　金：国家自然科学基金项目(51805253);国家重点研发计划项目(2018YFE0177000);国防基础科研项目(JCKY2018605C003)。

摘　　要：为解决分布式多工厂生产调度问题,将其转化为分布式柔性车间调度问题,设计了基于二阶振荡的随机权重混合粒子群算法,以最小化、最大完工时间为目标,将柔性作业车间调度问题嵌套于分布式调度方式中进行求解,利用随机权重来平衡全局和局部搜索能力,运用学习因子的二阶振荡提高全局搜索能力,并通过算例仿真验证了该算法的有效性和优越性。To improve the distributed multi-plants production scheduling by converting it into a distributed and flexible job shop scheduling,a second-order oscillation-based random-weighted hybrid particle swarm optimization algorithm was designed.With the goal of minimizing the makespan,the flexible job shop scheduling problem was solved as a sub-problem of the distributed scheduling problem.Random weight was adopted to balance the global and local search capability,and the second-order oscillation of the learning factor was applied to improve the global search capability.The simulation results verify the effectiveness and superiority of the algorithm.

关 键 词：分布式多工厂 改进粒子群算法 二阶振荡 随机权重 最大完工时间 

分 类 号：TH165[机械工程—机械制造及自动化]