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  • 标题:MINIMIZE THE MAKESPAN FOR JOB SHOP SCHEDULING PROBLEM USING ARTIFICIAL IMMUNE SYSTEM APPROACH
  • 本地全文:下载
  • 作者:AHMAD SHAHRIZAL MUHAMAD ; SAFAAI DERIS ; ZALMIYAH ZAKARIA
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2015
  • 卷号:80
  • 期号:1
  • 出版社:Journal of Theoretical and Applied
  • 摘要:In the manufacturing industry, scheduling is a process of arranging, controlling and optimizing work and workloads in a production process. This research discussed about job-shop scheduling problem. The main problem in job-shop scheduling is to optimize the usage of machines in order to obtain the shortest time in completing the activities. Several methods have been used to solve job-shop scheduling problems and the method proposed here is artificial intelligence by using the artificial immune system algorithm (AIS). The advantage of this algorithm is fabricated by imitating the natural immune system. The results produced by this method are compared with the best results of the previous research.
  • 关键词:Scheduling; Artificial Intelligence; Job-shop Scheduling; Artificial Immune System; Evolutionary Computation
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