Genetic algorithm approach for solving a cell formation problem in cellular manufacturing

  • Authors:

  • Iraj Mahdavi;Mohammad Mahdi Paydar;Maghsud Solimanpur;Armaghan Heidarzade

  • Affiliations:

  • Department of Industrial Engineering, Mazandaran University of Science and Technology, Tabarsi Street, Babol 47166-95635, Iran;Department of Industrial Engineering, Mazandaran University of Science and Technology, Tabarsi Street, Babol 47166-95635, Iran;Faculty of Engineering, Urmia University, Urmia, Iran;Department of Industrial Engineering, Mazandaran University of Science and Technology, Tabarsi Street, Babol 47166-95635, Iran and Department of Industrial Engineering, Payame Noor University, Sar ...

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Cellular manufacturing (CM) is an industrial application of group technology concept. One of the problems encountered in the implementation of CM is the cell formation problem (CFP). The CFP attempted here is to group machines and parts in dedicated manufacturing cells so that the number of voids and exceptional elements in cells are minimized. The proposed model, with nonlinear terms and integer variables, cannot be solved for real sized problems efficiently due to its NP-hardness. To solve the model for real-sized applications, a genetic algorithm is proposed. Numerical examples show that the proposed method is efficient and effective in searching for optimal solutions. The results also indicate that the proposed approach performs well in terms of group efficacy compared to the well-known existing cell formation methods.