文章基本信息

标题：Analysis of Genetic Algorithm for Multiprocessor Task Scheduling Problem
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作者：Bhawna Gupta ; Sunita Dhingra
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：7
出版社：S.S. Mishra
摘要：Multiprocessor task scheduling (MPTS) is an important and computationally difficult problem. Multiprocessors have emerged as a powerful computing means for running real-time applications. The problem of task scheduling on multiprocessor systems is known to be NP-complete in general.Genetic algorithm (GA) is one of the widely used techniques for constrained optimization. Genetic algorithms are known to provide robust, stochastic solutions for numerous optimization problems. The results of experimental comparison of six different combinations of crossover (i.e. PMX, OX and CX) and mutation (i.e. Insertion, Swap) operators for the MPTS are presented. In this paper, the experimental results shows that PMX and Insertion Mutation combination enables to achieve a better solution than other operators combination tested
关键词：Genetic Algorithm (GA); crossover; mutation; Multiprocessor task scheduling (MPTS); permutation flow shop ;scheduling.