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  • 标题:A Hybrid Genetic Algorithm for Pallet Loading in Real-World Applications
  • 本地全文:下载
  • 作者:Gabriele Ancora ; Gianluca Palli ; Claudio Melchiorri
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:10006-10010
  • DOI:10.1016/j.ifacol.2020.12.2719
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper addresses the so called ”Distributor’s Pallet Packing Problem” in a real industrial scenario. The main goal is to develop an algorithm for loading heterogeneous rectangular boxes on a bin, minimizing some objective functions and also satisfying geometric, stability and fragility constraints. The algorithm must be able to provide, in a reasonable time, the spatial coordinates of the vertices of the placed boxes and also the optimal boxes input sequence. Since this type of combinatorial problem is classified as NP-hard, classical optimization techniques are not suitable. For these reasons, a metaheuristic approach has been developed in order to reduce burden complexity. In particular, a genetic algorithm hybridized with an innovative heuristic technique has been used. The validity and the performance of this algorithm have been tested on several packing instances (orders) provided by an industrial company. The paper is intended as a preliminary study for future developments in the area of industrial container loading problems.
  • 关键词:Keywordsgenetic algorithmmetaheuristic techniquesNP-hard problemsoptimizationpacking problems
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