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  • 标题:Genetic Algorithm Approaches for CPU Scheduling in Operating System
  • 本地全文:下载
  • 作者:Manu Sharma ; Preeti Sindhwani ; Vijay Maheshwari
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2013
  • 卷号:4
  • 期号:2
  • 页码:211-213
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:To increase the performance of CPU and to get maximum throughput, there are many scheduling approaches which are been used in terms of scheduling the processes, waiting in the ready queue for their chances to get processed. This paper presents the genetic algorithm approach to provide the near to optimal solution for scheduling the processes. CPU scheduling is an NP hard problem. Genetic algorithm provides the optimal solution to these NP hard problems. These algorithms handle a population of possible solutions and the selection of these solutions is based on the fitness function. Crossoverandother operators are used to generate the fittest population. This paper compares the traditional CPU scheduling algorithm approaches according to their average waiting time with GA based scheduling algorithm to find the optimal solution.
  • 关键词:Genetic Algorithm;NP hard;Crossover;Mutation;gene
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