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Generalized cell formation: iterative versus simultaneous resolution with grouping genetic algorithm

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Abstract

For each industrial, lean manufacturing is “The method” to improve productivity and reduce cost. One of the tools for lean is cellular manufacturing. This technique reduces the factory to several small entities which are easier to manage. The algorithm proposed in this paper is based on a simultaneous resolution of two interdependent problems. These two problems emerge when the flexibility is used during the production process. This paper proves the efficiency of the simultaneous resolution comparing to the sequential resolution with iterations. To compare only the resolution method, a unique grouping genetic algorithm is adapted to be used in both cases.

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Notes

  1. PFA provides well-established, efficient and analytical engineering method for planning the change from process organization to product organization.

  2. The reviews of Mansouri et al. (2000) and Defersha and Chen (2006) incorporate a wider range of input data and cell formation criteria.

  3. The complete case can available by email.

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  1. Université Libre de Bruxelles, 50 Avenue Franklin Roosevelt—CP 165/56, B-1050, Brussels, Belgium

    Emmanuelle Vin & Alain Delchambre

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  1. Emmanuelle Vin
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  2. Alain Delchambre
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Correspondence to Emmanuelle Vin.

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Vin, E., Delchambre, A. Generalized cell formation: iterative versus simultaneous resolution with grouping genetic algorithm. J Intell Manuf 25, 1113–1124 (2014). https://doi.org/10.1007/s10845-013-0749-7

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  • DOI: https://doi.org/10.1007/s10845-013-0749-7

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