文章基本信息

标题：GENETIC ALGORITHM FOR MULTIPROCESSOR TASK SCHEDULING
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作者：Ritu Verma ; Sunita Dhingra
期刊名称：International Journal of Computer Science and Management Studies
电子版ISSN：2231-5268
出版年度：2011
卷号：11
期号：2
出版社：Imperial Foundation
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 especially due to limitation of uni-processor system for not having sufficient enough capability to execute all the tasks. This paper describes multiprocessor task scheduling in the form of permutation flow shop scheduling, which has an objective function for minimizing the makespan. Here, we will conclude how the performance of genetic algorithms (value of the makespan of the schedule) varies with the variation of Genetic Algorithm (GA) control parameters (population size, crossover probability and mutation probability).
关键词：Genetic Algorithm (GA); crossover; mutation; Multiprocessor task scheduling (MPTS); permutation flow shop scheduling