文章基本信息

标题：AN OVERVIEW OF GENETIC ALGORITHM FOR TASK SCHEDULING ON MULTIPROCESSORS
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作者：Bhawna Gupta ; Sunita Dhingra
期刊名称：International Journal of Computer Science and Management Studies
电子版ISSN：2231-5268
出版年度：2013
卷号：13
期号：4
出版社：Imperial Foundation
摘要：Multiprocessor task scheduling is an important and computationally difficult problem. Multiprocessors have emerged as a powerful computing means for running real-time applications. That computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. These tasks should be assigned in a way such that the total execution time is minimized and certain criteria are met. The problem of task scheduling on multiprocessor systems is known to be NP-complete in general. Solving this problem using by conventional techniques needs reasonable amounts of time a wide range of solutions and heuristics have been proposed to solve this important system optimization problem. 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. To get the positive results we have some operators (crossover and mutation) in genetic algorithm that must be adjusted properly. In this paper, the basic conceptual features and specific characteristics of various crossover and mutation operators are discussed.
关键词：Multiprocessor scheduling; genetic algorithm; crossover; mutation