首页> 外文会议>International Conference on Computational Intelligence >A Comparison Between Genetic Algorithm and Cuckoo Search Algorithm to Minimize the Makespan for Grid Job Scheduling
【24h】

A Comparison Between Genetic Algorithm and Cuckoo Search Algorithm to Minimize the Makespan for Grid Job Scheduling

机译:遗传算法与杜鹃搜索算法的比较,最大限度地减少网格作业调度的Makespan

获取原文

摘要

Major subjects like heterogeneity of resources, dynamic and autonomous character of Grid resources are most important challenges for Grid job scheduling. Additionally, there are issues of various strategies being maintained by the resource providers and followed by resource users for execution of their jobs. Thus optimal job scheduling is an NP-complete problem which can easily be solved by using heuristic approaches. This paper compares two heuristic methods: Genetic Algorithm (GA) and Cuckoo Search Algorithm (CSA) for job scheduling problem in order to efficiently allocating jobs to resources in a Grid system so that the makespan is minimized. Our empirical results have proved that the CSA performs better than the GA.
机译:像资源的异质性,电网资源的动态和自主特征等主要科目是网格职位调度的最重要挑战。 此外,资源提供商存在各种策略的问题,然后是资源用户执行工作的各种策略。 因此,最佳工作调度是一种NP完整问题,可以通过使用启发式方法轻松解决。 本文比较了两种启发式方法:遗传算法(GA)和Cuckoo搜索算法(CSA)用于作业调度问题,以便将作业有效地分配给网格系统中的资源,以便最小化MEPESPAN。 我们的经验结果证明,CSA比GA更好。

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