A computational study of hybrid approaches of metaheuristic algorithms for the cell formation problem

Luong Thuan Thanh, Jacques A. Ferland, Bouazza Elbenani, Nguyen Dinh Thuc, Van Hien Nguyen

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we solve the 0-1 cell formation problem where the number of cells is fixed a priori and where the objective is to maximize the overall efficiency of a production system by grouping together machines providing service to similar parts into a subsystem (denoted cell). Three different methods are introduced and compared numerically. The first local search method is an implementation of simulated annealing (SA) where the definition of the neighbourhood is specific to the application and requires using a diversification and intensification strategies. The second local search method is an adaptive simulated annealing method where the neighbourhood is selected randomly at each iteration. The procedure is adaptive in the sense that the probability of selecting a neighbourhood is updated during the process. The third method is a hybrid method (HM) of a population-based method and a local search method. To improve the solution obtained with HM, we apply a SA method afterward. The best variants are very efficient to solve the 35 benchmark problems commonly used in the literature.

Original languageEnglish
Pages (from-to)20-36
Number of pages17
JournalJournal of the Operational Research Society
Volume67
Issue number1
DOIs
Publication statusPublished - 1 Jan 2016

Keywords

  • combinatorial optimization
  • Evolutionary computation
  • fractional programming
  • genetic algorithm
  • simulated annealing

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