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  • 标题:Car sequencing problem with cross-ratio constraints: A multi-start parallel local search
  • 本地全文:下载
  • 作者:M. Mahmoodjanloo ; A. Baboli ; M. Ruhla
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:10
  • 页码:1255-1260
  • DOI:10.1016/j.ifacol.2022.09.562
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Car sequencing is a popular approach to implicitly improve the short-term balancing of a mixed-model assembly line in real-world applications. In this paper, based on a real-world case from a truck final assembly line, we study this problem considering cross-ratio constraints which concern the limitations of some dependent features of products. A mathematical programming model is developed to minimize the total weighted penalty of disrespecting the independent and dependent limitations. Since the problem is NP-hard, a multi-start parallel local search is developed to efficiently solve the problem. A comparison of the results illustrates the effectiveness of using the proposed algorithm.
  • 关键词:Mixed-model assembly line;Sequencing problem;Parallel variable neighborhood search;Multi-agent algorithm
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