基于微粒群算法的柔性流水车间调度优化

中国机械工程 ›› 2010, Vol. 21 ›› Issue (9): 1053-1057.

基于微粒群算法的柔性流水车间调度优化

周辉仁1;唐万生1;魏颖辉2

1.天津大学,天津,300072

2.辽宁科技学院,本溪,117022

出版日期:2010-05-10 发布日期:2010-05-19
基金资助:
中国博士后科学基金资助项目(20090450759)；辽宁省教育厅科研课题资助项目(20060439)
Supported by China Postdoctoral Science Foundation（No. 20090450759）;
Liaoning Provincial Scientific Research Project of Ministry of Education of China（No. 20060439）

PSO-based Optimization of Flexible Flow-shop Scheduling

Zhou Huiren1;Tang Wansheng1;Wei Yinghui2

1.Tianjin University, Tianjin, 300072

2.Liaoning Institute of Science and Technology, Benxi,Liaoning,117022

Online:2010-05-10 Published:2010-05-19
Supported by:

Supported by China Postdoctoral Science Foundation（No. 20090450759）;
Liaoning Provincial Scientific Research Project of Ministry of Education of China（No. 20060439）

摘要/Abstract

摘要：

为了有效地解决柔性Flow-shop调度问题,提出用改进的微粒群算法进行求解,给出了一种能够保证个体合法性的编码方法;提出速度的计算公式采用自适应惯性权重和收缩因子相结合的方法。最后以某汽车发动机厂金加工车间的生产调度实例进行仿真,比较结果表明该算法的效果较好。

关键词:

柔性Flow-shop调度, 微粒群算法, 编码方法, 自适应惯性权重

Abstract:

In order to solve FFS problem efficiently, a new method solving FFS problem based on improved PSO algorithm was used. A new improved encoding method for the FFS problem could avoid illegal solution. The velocity formula adopting an adaptive inertia weight and constriction factor was proposed. Finally, an example of production scheduling problem for metalworking workshop in a car engine plant was simulated. Through comparison, the results show the effectiveness of the algorithm.

Key words: flexible flow-shop scheduling(FFS), particle swarm optimization(PSO), encoding method, adaptive inertia weight

中图分类号:

TP278

周辉仁, 唐万生, 魏颖辉.

基于微粒群算法的柔性流水车间调度优化

[J]. 中国机械工程, 2010, 21(9): 1053-1057.

ZHOU Hui-Ren, TANG Mo-Sheng, WEI Ying-Hui.

PSO-based Optimization of Flexible Flow-shop Scheduling

[J]. China Mechanical Engineering, 2010, 21(9): 1053-1057.

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