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  • 标题:Performance Evaluation of PSO, PSOCA and MPSOCA for Solving University Timetabling Problem
  • 本地全文:下载
  • 作者:Oluwaseun O. Alade ; Christopher A. Oyeleye ; Oluyinka T. Adedeji
  • 期刊名称:Annals. Computer Science Series
  • 印刷版ISSN:1583-7165
  • 电子版ISSN:2065-7471
  • 出版年度:2018
  • 卷号:16
  • 期号:2
  • 页码:149-154
  • 出版社:Mirton Publishing House, Timisoara
  • 摘要:

    In this paper, performance evaluation of Particle Swarm Optimization algorithm (PSO), Particle Swarm Optimization based Cultural Algorithm (PSOCA) and Modified Particle Swarm Optimization based Cultural Algorithm (MPSOCA) was carried out using simulation time, fitness value and number of unallocated courses as performance metrics. The evaluation results of PSO, PSOCA and MPSOCA yielded average simulation times of 35.29, 37.68 and 17.42 seconds, respectively. Also, fitness values of 85, 89 and 90% were recorded for PSO, PSOCA and MPSOCA, respectively. PSO have a total average number of 60 subjects unallocated compare to PSOCA and MPSOCA that successfully allocated all the subjects.

  • 关键词:Particle Swarm Optimization Algorithm; Cultural Algorithm; Timetabling.
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