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A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach

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Abstract

A comprehensive multi-objective mathematical programming model is proposed in this paper to design a cellular manufacturing system. The model considers machine redundancy, production volume, processing time, cost of machines, sequence of operations, and alternative processing plans. A fuzzy goal programming approach is used to convert the proposed multi-objective model into a single-objective one. Due to NP-hard nature of the model, a genetic algorithm is developed for solving the proposed model. Performance of the proposed genetic algorithm is evaluated by adopting four problems from literature. The results indicate effectiveness and efficiency of the proposed algorithm in comparison with those obtained by Lingo and NSGA-II algorithm.

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Correspondence to Shahram Saeidi.

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Saeidi, S., Solimanpur, M., Mahdavi, I. et al. A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach. Int J Adv Manuf Technol 70, 1635–1652 (2014). https://doi.org/10.1007/s00170-013-5392-0

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Keywords

  • Cell formation problem
  • Cellular manufacturing
  • Group technology
  • Fuzzy goal programming
  • Genetic algorithm
  • NSGA-II