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 journalArticle

9 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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