A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

Forough Zarea Fazlelahi, Mehrdokht Pournader*, Mohsen Gharakhani, Seyed Jafar Sadjadi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm-robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Original languageEnglish
Pages (from-to)2264-2274
Number of pages11
JournalProceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
Volume230
Issue number12
DOIs
Publication statusPublished - 1 Dec 2016

Keywords

  • Dynamic facility layout problem
  • intra-cellular manufacturing
  • permutation-based genetic algorithm
  • robust optimization

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