吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

离散粒子群优化算法在流水作业调度问题中的应用

付志军1, 冯丽2, 杜伟宁3, 凌振宝1, 杨凤芹4   

  1. 1. 吉林大学 仪器科学与电气工程学院, 长春 130061; 2. 安阳师范学院 数学与统计学院, 河南 安阳 455002;3. 空军航空大学 飞行训练基地, 长春 130062; 4. 东北师范大学 计算机科学与信息技术学院, 长春 130117
  • 收稿日期:2013-10-11 出版日期:2014-05-26 发布日期:2014-08-27
  • 通讯作者: 付志军 E-mail:fuzj11@mails.jlu.edu.cn

Applications of Discrete Particle Swarm Optimization inSolving the JobShop Scheduling Problems

FU Zhijun1,  FENG Li2, DU Weining3, LING Zhenbao1,  YANG Fengqin4   

  1. 1. College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130061, China;2. School of Mathematics and Statistic, Anyang Normal University, Anyang 455002, Henan Province, China;3. Flight Training Basic, Aviation University of Air Force, Changchun 130062, China;4. School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
  • Received:2013-10-11 Online:2014-05-26 Published:2014-08-27
  • Contact: FU Zhijun E-mail:fuzj11@mails.jlu.edu.cn

摘要:

通过引入随机向量, 改进离散粒子群算法DPSO的更新方程, 提出一种离散的粒子群优化算法MDPSO, 并将其应用于调度问题的求解. 实验结果表明, 该算法优于传统的时序分解算法和遗传算法.

关键词: 进化算法, 粒子群优化算法, 调度问题

Abstract:

A novel particle swarm optimization (DPSO) algorithm for solving the flexible jobshop scheduling (FJSP) was proposed by introducing random vector to improve the updating equation of DPSO. The experiments show that the proposed algorithm is superior to the temporal decomposition method and the
 classic genetic method.

Key words: evolutionary algorithm, particle swarm optimization algorithm, scheduling problem

中图分类号: 

  • TP181