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A fuzzy multi-objective model for a cellular manufacturing system with layout designing in a dynamic condition

Author

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  • Ali Mohtashami
  • Alireza Alinezhad
  • Amir Hossein Niknamfar

Abstract

Cellular manufacturing system (CMS) plays a remarkably significant role in modern production systems. This paper presents a novel and practical fuzzy multi-objective mathematical model for a CMS in a dynamic condition considering the flexibility in allocating machines. The proposed model seeks to determine the best layout design in each production period. Two conflicting objectives are considered including minimising the cost of manufacturing system due to the amount of production loss caused by waste, as well as minimising the variance of fuzzy costs. Due to the complexity of the problem, non-dominate sorting genetic algorithm-II and multi-objective particle swarm optimisation algorithm are designed to solve the model and to obtain the effective solutions. In order to demonstrate the efficiency of the algorithms and to choose the premier algorithm, both algorithms are evaluated in several A fuzzy multi-objective model for a cellular manufacturing system 515 random problems and then compared based on the existing measurement indicators. Then, the algorithms are tuned to solve the problem, based on which their performances are analysed statistically. The applicability of the proposed approach and the solution methodologies are demonstrated as well.

Suggested Citation

  • Ali Mohtashami & Alireza Alinezhad & Amir Hossein Niknamfar, 2020. "A fuzzy multi-objective model for a cellular manufacturing system with layout designing in a dynamic condition," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 34(4), pages 514-543.
    • Handle: RePEc:ids:ijisen:v:34:y:2020:i:4:p:514-543
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    Cited by:

    1. Alhawari, Omar I. & Süer, Gürsel A. & Bhutta, M. Khurrum S., 2021. "Operations performance considering demand coverage scenarios for individual products and products families in supply chains," International Journal of Production Economics, Elsevier, vol. 233(C).

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