An improved genetic algorithm with limited iteration for Grid scheduling

被引：9
|
作者：
Yin, Hao [1 ,2 ]
Wu, Huilin [2 ]
Zhou, Jiliu [1 ,2 ]
机构：
[1] Sichuan Univ, Sch Comp Sci, 24 S Sect 1,Yihuan Rd, Chengdu 610065, Peoples R China
[2] Sichuan Univ, Sch Elect Informat, Chengdu 610065, Peoples R China
来源：
SIXTH INTERNATIONAL CONFERENCE ON GRID AND COOPERATIVE COMPUTING, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/GCC.2007.42
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：221 / +
页数：2
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