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文章基本信息

  • 标题:Stochastic local search: a state-of-the-art review
  • 本地全文:下载
  • 作者:Muhamet Kastrati ; Marenglen Biba
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2021
  • 卷号:11
  • 期号:1
  • 页码:716
  • DOI:10.11591/ijece.v11i1.pp716-727
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stochastic local search techniques used for solving hard combinatorial problems. It begins with a short introduction, motivation and some basic notation on combinatorial problems, search paradigms and other relevant features of searching techniques as needed for background. In the following a brief overview of the stochastic local search methods along with an analysis of the state-of-the-art stochastic local search algorithms is given. Finally, the last part of the paper present and discuss some of the most latest trends in application of stochastic local search algorithms in machine learning, data mining and some other areas of science and engineering. We conclude with a discussion on capabilities and limitations of stochastic local search algorithms.
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