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  • 标题:Simulation-Based EDAs for Stochastic Programming Problems
  • 本地全文:下载
  • 作者:Abdel-Rahman Hedar ; Amira A. Allam ; Alaa E. Abdel-Hakim
  • 期刊名称:Computation
  • 电子版ISSN:2079-3197
  • 出版年度:2020
  • 卷号:8
  • 期号:1
  • 页码:18-36
  • DOI:10.3390/computation8010018
  • 出版社:MDPI Publishing
  • 摘要:With the rapid growth of simulation software packages, generating practical tools for simulation-based optimization has attracted a lot of interest over the last decades. In this paper, a modified method of Estimation of Distribution Algorithms (EDAs) is constructed by a combination with variable-sample techniques to deal with simulation-based optimization problems. Moreover, a new variable-sample technique is introduced to support the search process whenever the sample sizes are small, especially in the beginning of the search process. The proposed method shows efficient results by simulating several numerical experiments.
  • 关键词:estimation of distribution algorithms; simulation-based optimization; stochastic programming; variable sample path estimation of distribution algorithms ; simulation-based optimization ; stochastic programming ; variable sample path
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