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Metaheuristic in facility layout problems: current trend and future direction

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  • Anirban Kundu
  • Pranab K. Dan

Abstract

A state-of-the-art review, spanning the last two decades, on application of metaheuristic methods in facility layout problems (FLPs) to gauge the current and emerging trends involving new design objectives, algorithms and methodologies to the combinatorial optimisation aspects is presented in this work. Fresh developments in emerging layout research, as analysed in this study, provide a perspective on what the future of the field will be like. A tendency of using metaheuristics, such as genetic algorithm (GA), simulated annealing (SA), ant colony optimisation (ACO) and particle swarm optimisation (PSO) with a trend towards multi-objective approaches to layout and material handling system design is observed.

Suggested Citation

  • Anirban Kundu & Pranab K. Dan, 2012. "Metaheuristic in facility layout problems: current trend and future direction," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 10(2), pages 238-253.
    • Handle: RePEc:ids:ijisen:v:10:y:2012:i:2:p:238-253
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    Citations

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    Cited by:

    1. Mowrey, Corinne H. & Parikh, Pratik J. & Gue, Kevin R., 2018. "A model to optimize rack layout in a retail store," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1100-1112.
    2. Karki, Uttam & Guthrie, Bradley & Parikh, Pratik J., 2021. "Joint determination of rack configuration and shelf space allocation for a retailer," International Journal of Production Economics, Elsevier, vol. 234(C).
    3. Qiaoyu Zhang & Yan Lin, 2024. "Integrating multi-agent reinforcement learning and 3D A* search for facility layout problem considering connector-assembly," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3393-3418, October.
    4. Jerzy Grobelny & Rafal Michalski, 2017. "A novel version of simulated annealing based on linguistic patterns for solving facility layout problems," WORking papers in Management Science (WORMS) WORMS/17/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    5. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2020. "A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 615-640, March.
    6. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2021. "3D facility layout problem," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1065-1090, April.

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