• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>World Congress on Intelligent Control and Automation;WCICA 2010 >Applied Research of Improved Hybrid Discrete PSO for Dynamic Job-shop Scheduling Problem
【24h】

Applied Research of Improved Hybrid Discrete PSO for Dynamic Job-shop Scheduling Problem

机译：改进的混合离散PSO在动态作业车间调度中的应用研究

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

By providing a detailed analysis of the particle swarm optimization (PSO) principle and job-shop scheduling problems, this paper presents a new hybrid discrete GAPSO combining the genetic strategy. Adjusting factors are introduced to regulate the generation of convergence; the proposed algorithm is tested by a set of benchmark problems. The results obtained show good convergence of the algorithm. On this basis, a new event-driven strategy for dynamic JSP is proposed, with regard to some uncertain dynamic events like inserting new jobs and machine failures, the proposed algorithm can reschedule once there occur uncertain dynamic events. The results of simulation have confirmed the effectiveness and feasibility of the improved hybrid discrete GAPSO algorithm.
机译：通过对粒子群优化（PSO）原理和车间调度问题进行详细分析，提出了一种结合遗传策略的新型混合离散GAPSO。引入调整因子来调节收敛的产生；所提出的算法通过一组基准问题进行了测试。所得结果表明该算法具有良好的收敛性。在此基础上，提出了一种新的事件驱动的动态JSP策略，针对一些不确定的动态事件，如插入新作业和机器故障，该算法可以在发生不确定的动态事件时重新调度。仿真结果证实了改进的混合离散GAPSO算法的有效性和可行性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号