An Improved Genetic Algorithm with Limited Iteration for Grid Scheduling

摘要：

In Grid environment the numbers of resources and tasks to be scheduled are usually variable. This kind of characteristics of grid makes the scheduling approach a complex optimization problem. Genetic algorithm (GA) has been widely used to solve these difficult NP-complete problems. However the conventional GA is too slow to be used in a realistic scheduling due to its time-consuming iteration. This paper presents an improved genetic algorithm for scheduling independent tasks in grid environment, which can increase search efficiency with limited number of iteration by improving the evolutionary process while meeting a feasible result.

作者: Hao Yin Huilin Wu Jiliu Zhou

作者单位: School of Computer Science, Sichuan University, No.24 South Section 1, Yihuan Road,Chengdu, 610065, School of Computer Science, Sichuan University, No.24 South Section 1, Yihuan Road,Chengdu, 610065, School of Computer Science, Sichuan University, No.24 South Section 1, Yihuan Road,Chengdu, 610065,

会议类型: 国际会议

会议名称: 第六届网格与协同计算国际会议(The Sixth International Conference on Grid and Cooperative Computing GCC 2007)

会议地点: 乌鲁木齐

会议语种:英文

页码: 221-227

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）