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A hybrid heuristic algorithm adopting both Boltzmann function and mutation operator for manufacturing cell formation problems

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  • Wu, Tai-Hsi
  • Chang, Chin-Chih
  • Yeh, Jinn-Yi

Abstract

This study proposes a hybrid heuristic algorithm employing both the Boltzmann function from simulated annealing and the mutation operator from the genetic algorithm to explore the unvisited solution region and expedite the solution searching process for the cell formation problem, so that grouping efficacy is maximized. Test problems drawn from the literature are used to test the performance of the proposed heuristic algorithm. The comparative study shows that the proposed algorithm improves the best results found in the literature for 36% of the test problems in the case when singletons solutions are allowed.

Suggested Citation

  • Wu, Tai-Hsi & Chang, Chin-Chih & Yeh, Jinn-Yi, 2009. "A hybrid heuristic algorithm adopting both Boltzmann function and mutation operator for manufacturing cell formation problems," International Journal of Production Economics, Elsevier, vol. 120(2), pages 669-688, August.
  • Handle: RePEc:eee:proeco:v:120:y:2009:i:2:p:669-688
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    References listed on IDEAS

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    1. Stanfel, Larry E., 1985. "Machine clustering for economic production," Engineering Costs and Production Economics, Elsevier, vol. 9(1-3), pages 73-81, April.
    2. Yin, Yong & Yasuda, Kazuhiko, 2006. "Similarity coefficient methods applied to the cell formation problem: A taxonomy and review," International Journal of Production Economics, Elsevier, vol. 101(2), pages 329-352, June.
    3. Mosier, Charles & Taube, Larry, 1985. "Weighted similarity measure heuristics for the group technology machine clustering problem," Omega, Elsevier, vol. 13(6), pages 577-579.
    4. Ravi Kumar, K. & Kusiak, Andrew & Vannelli, Anthony, 1986. "Grouping of parts and components in flexible manufacturing systems," European Journal of Operational Research, Elsevier, vol. 24(3), pages 387-397, March.
    5. William T. McCormick & Paul J. Schweitzer & Thomas W. White, 1972. "Problem Decomposition and Data Reorganization by a Clustering Technique," Operations Research, INFORMS, vol. 20(5), pages 993-1009, October.
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    Cited by:

    1. Pinheiro, Rian G.S. & Martins, Ivan C. & Protti, Fábio & Ochi, Luiz S. & Simonetti, Luidi G. & Subramanian, Anand, 2016. "On solving manufacturing cell formation via Bicluster Editing," European Journal of Operational Research, Elsevier, vol. 254(3), pages 769-779.
    2. Juan Díaz & Dolores Luna & Ricardo Luna, 2012. "A GRASP heuristic for the manufacturing cell formation problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 679-706, October.
    3. Yu, Yang & Tang, Jiafu & Sun, Wei & Yin, Yong & Kaku, Ikou, 2013. "Reducing worker(s) by converting assembly line into a pure cell system," International Journal of Production Economics, Elsevier, vol. 145(2), pages 799-806.
    4. Lin, Shih-Wei & Ying, Kuo-Ching & Lu, Chung-Cheng & Gupta, Jatinder N.D., 2011. "Applying multi-start simulated annealing to schedule a flowline manufacturing cell with sequence dependent family setup times," International Journal of Production Economics, Elsevier, vol. 130(2), pages 246-254, April.

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