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An immune system based algorithm for cell formation problem

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  • Berna H. Ulutas

    (Eskisehir Osmangazi University)

Abstract

Technological developments enable the design and manufacturing of products tailored to individual consumers. Cellular Manufacturing Systems (CMS) can be considered as to ease flexibility, to reduce setup time, throughput time, work-in-process inventories, and material handling costs. Cell formation problem (CFP) that is one of the critical CMS design problems is the assignment of parts and machines to specific cells based on their similarity. This study introduces a Clonal Selection Algorithm (CSA) with a novel encoding structure that is efficient to solve real-sized problems. Unlike the methods in literature that define the number of cells as a constant number, this algorithm is significant because it can obtain the optimum number of cell to generate best efficacy value. Proposed CSA is tested by using 67 (35 well-known and 32 less-known) test problems. CSA obtains the same 63 best-known optimal solutions, provides solutions for the 3 of the well-known test problem and a new solution for the largest test problem (50 machine 150 part) that was not possible to be solved by the mixed integer linear programming model due to the high computational complexity. Final CSA grouping results are illustrated with figures to attract attention to the singleton and residual cells.

Suggested Citation

  • Berna H. Ulutas, 2019. "An immune system based algorithm for cell formation problem," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2835-2852, December.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:8:d:10.1007_s10845-018-1407-x
    DOI: 10.1007/s10845-018-1407-x
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    References listed on IDEAS

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    1. Mosier, Charles & Taube, Larry, 1985. "Weighted similarity measure heuristics for the group technology machine clustering problem," Omega, Elsevier, vol. 13(6), pages 577-579.
    2. Papaioannou, Grammatoula & Wilson, John M., 2010. "The evolution of cell formation problem methodologies based on recent studies (1997-2008): Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 206(3), pages 509-521, November.
    3. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    4. Yang, Miin-Shen & Yang, Jenn-Hwai, 2008. "Machine-part cell formation in group technology using a modified ART1 method," European Journal of Operational Research, Elsevier, vol. 188(1), pages 140-152, July.
    5. Li, Ming-Liang, 2003. "The algorithm for integrating all incidence matrices in multi-dimensional group technology," International Journal of Production Economics, Elsevier, vol. 86(2), pages 121-131, November.
    6. Stanfel, Larry E., 1985. "Machine clustering for economic production," Engineering Costs and Production Economics, Elsevier, vol. 9(1-3), pages 73-81, April.
    7. J. E. King, 1999. "Introduction," Review of Political Economy, Taylor & Francis Journals, vol. 11(3), pages 251-255.
    8. X-Y Li & Y P Aneja & F Baki, 2010. "An ant colony optimization metaheuristic for single-path multicommodity network flow problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(9), pages 1340-1355, September.
    9. 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.
    10. 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:

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