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文章基本信息

  • 标题:Tabu Search Algorithms for Multimodal and Multi-Objective Function Optimizations
  • 本地全文:下载
  • 作者:Masakazu Takahashi ; Setsuya Kurahashi
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2007
  • 卷号:7
  • 期号:10
  • 页码:257-264
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:The integration of genetic algorithms (GAs) and tabu search is one of the traditional problems in function optimization in the GA literature. However, most of the proposed methods have utilized genetic algorithms to explore global candidates and tabu search to exploit local optimal points. Unlike such methods so far, this paper proposes a new algorithm to directly store individuals into multiple tabu lists during GA-iterations. The tabu lists inhibit similar solution candidates from being selected so often. The proposed algorithm is so simple but strong that we can solve both multimodal and multi-objective problems in the same manner. This paper describes the basic idea, algorithms, and experimental results. One of the applications for this algorithm will be suitable for the recommendation of the grocery items among the retail businesses.
  • 关键词:Generic Algorithms, Tabu Search, Multi-modal Function Optimization, Multi-Objective Problems, Social System Simulation
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