期刊文献+

基于改进遗传算法的FlowShop调度算法研究

Research on Flow Shop Scheduling Problem Based on Improved Genetic Algorithm
下载PDF
导出
摘要 给出了Flow Shop调度问题的数学模型,介绍了三种用于求解该问题的启发式算法,根据普通遗传算法与启发式算法的互补特性,提出了结合两者各自优势的改进遗传算法.通过两个不同规模的经典算例对算法的优化性能进行了对比分析,结果表明,采用了保优策略的改进遗传算法的搜索能力优于启发式算法及普通遗传算法,并具有较强的鲁棒性. This paper introduces a mathematical model of Flow Shop Problem(FSP), and then gives three heuristic algorithms to solve it. The new improved Genetic Algorithm(GA) is presented by combining the advantages of standard GA and heuristic algorithm. With two benchmark FSPs, the simulation results show that the new method of GA by using elitist selection strategy has better performance than standard GA and heuristic algorithm, and has strong robustness.
出处 《宁夏大学学报(自然科学版)》 CAS 北大核心 2007年第4期322-325,共4页 Journal of Ningxia University(Natural Science Edition)
关键词 遗传算法 流水作业调度 启发式算法 genetic algorithm flow shop scheduling heuristic algorithm
  • 相关文献

参考文献4

  • 1房育栋,郝建忠,余英林,温玉汉.遗传算法及其在TSP中的应用[J].华南理工大学学报(自然科学版),1994,22(3):124-127. 被引量:6
  • 2JOHNSON S. Optimal two-and-three stage production schedules with setup times include[J]. Naval Research Logistics Puarterly, 1954, 1: 61-68.
  • 3DUBDEK R, PANWALKAR S, SMITH M. The lessons of flow shop scheduling research[J].Operation Research, 1992, 40: 7-13.
  • 4CHEN C, VEMPATI V, ALJABER N. An application of genetic algorithms for flow shop problems[J]. European Journal of Operational Research, 1995, 80: 389-396.

二级参考文献4

共引文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部