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Reconfigurable Dynamic Cellular Manufacturing System: A NewBi-Objective Mathematical Model

Published online by Cambridge University Press:  10 January 2014

Masoud Rabbani ,
Mehran Samavati ,
Mohammad Sadegh Ziaee  and
Hamed Rafiei
Masoud Rabbani
Affiliation:
School of Industrial & Systems Engineering, College of Engineering, University of Tehran, North Kargar St., P.O. Box: 11155-4563, Tehran, Iran.. mrabani@ut.ac.ir; mehransamavati@ut.ac.ir; hrafiei@ut.ac.ir
Mehran Samavati
Affiliation:
School of Industrial & Systems Engineering, College of Engineering, University of Tehran, North Kargar St., P.O. Box: 11155-4563, Tehran, Iran.. mrabani@ut.ac.ir; mehransamavati@ut.ac.ir; hrafiei@ut.ac.ir
Mohammad Sadegh Ziaee
Affiliation:
Faculty of Management, University of Tehran, Tehran, Iran.; ziaee@ut.ac.ir
Hamed Rafiei
Affiliation:
School of Industrial & Systems Engineering, College of Engineering, University of Tehran, North Kargar St., P.O. Box: 11155-4563, Tehran, Iran.. mrabani@ut.ac.ir; mehransamavati@ut.ac.ir; hrafiei@ut.ac.ir
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Abstract

Dynamic Cell Formation Problem (DCFP) seeks to cope with variation in part mix anddemands using machine relocation, replication, and removing; whilst from practical pointof view it is too hard to move machines between cells or invest on machine replication. Tocope with this deficiency, this paper addresses Reconfigurable Dynamic Cell FormationProblem (RDCFP) in which machine modification is conducted instead of their relocation orreplication in order to enhance machine capabilities to process wider range of productiontasks. In this regard, a mixed integer nonlinear mathematical model is proposed, which isNP-hard. To cope with the proposed model’s intractability, an Imperialist CompetitiveAlgorithm (ICA) is developed, whose obtained results are compared with those of GeneticAlgorithm’s (GA’s), showing superiority and outperformance of the developed ICA.

Keywords

Dynamic cell formation problemgenetic algorithmimperialist competitive algorithmmachine modificationreconfigurable cellular manufacturing system

Information

Type
Research Article
Information
RAIRO - Operations Research , Volume 48 , Issue 1 , January 2014 , pp. 75 - 102
Copyright
© EDP Sciences, ROADEF, SMAI, 2014

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References

J.A. Tompkins, J.A. White, Y.A. Bozer and J.M.A. Tanchoco, Facilities Planning. Wiley, USA (2003).
Balakrishnan, J. and Cheng, C.H., Multi-period planning and uncertainty issues in cellular manufacturing: A review and future research directions. Eur. J. Oper. Res. 177 (2007) 281–309. Google Scholar
Rheault, M., Drolet, J.R. and Abdulnour, G., Physically reconfigurable virtual cells: A dynamic model for a highly dynamic environment. Comput. Ind. Eng. 29 (1995) 221–225. Google Scholar
Saxena, L.K. and Jain, P.K., Dynamic cellular manufacturing systems design-a comprehensive model. Int. J. Adv. Manuf. Technol. 53 (2011) 11–34. Google Scholar
Foulds, L.R., French, A.P. and Wilson, J.M., The sustainable cell formation problem: manufacturing cell creation with machine modification costs. Comput. Oper. Res. 33 (2006) 1010–1032. Google Scholar
Koren, Y., Heisel, U., Jovane, F., Moriwaki, T., Pritschow, G., Ulsoy, G. and Van Brussel, H., Reconfigurable Manufacturing Systems. Ann. CIRP 48 (1999) 1–14. Google Scholar
Mehrabi, M.G., Ulsoy, A.G. and Koren, Y., Reconfigurable manufacturing systems: key to future manufacturing. J. Intelligent Manuf. 11 (2000) 403–419. Google Scholar
Grahl, C.L., Increasing efficiencies with synthetic dies. Ceramic Ind. 151 (2001) 31–32. Google Scholar
Purcheck, G.F.K., A mathematical classification as a basis for the design of group technology production cells. Prod. Eng. 54 (1974) 35–48. Google Scholar
Kusiak, A., The generalized group technology concept. Int. J. Prod. Res. 25 (1987) 561–569. Google Scholar
Shtub, A., Modeling group technology cell formation as a generalized assignment problem. Int. J. Prod. Res. 27 (1989) 775–782. Google Scholar
Wei, J.C. and Gaither, N., A capacity constrained multi objective cell formation method. J. Manuf. Syst. 9 (1990) 222–232. Google Scholar
Song, S. and Hitomi, K., Integrating the production planning and cellular layout for flexible cell formation. Prod. Plan. Control. 7 (1996) 585–593. Google Scholar
Safaei, N., Saidi–Mehrabad, M. and Jabal–Ameli, M.S., A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. Eur. J. Oper. Res. 185 (2008) 563–592. Google Scholar
Ghotboddini, M.M., Rabbani, M. and Rahimian, H., A comprehensive dynamic cell formation design: Benders’ decomposition approach. Exp. Syst. Appl. 38 (2011) 2478–2488. Google Scholar
Kusiak, A., The generalized group technology concept. Int. J. Prod. Res. 25 (1987) 561–569. Google Scholar
Shtub, A., Modeling group technology cell formation as a generalized assignment problem. Int. J. Prod. Res. 27 (1989) 775–782. Google Scholar
Mahdavia, I., Aalaei, A., Paydar, M.M. and Solimanpur, M., Designing a mathematical model for dynamic cellular manufacturing systems considering production planning and worker assignment. Comput. Math. Appl. 60 (2010) 1014–1025. Google Scholar
Satoglu, S.I. and Suresh, N.C., A goal-programming approach for design of hybrid. Comput. Ind. Eng. 56 (2009) 560–575. Google Scholar
A. Mungwattana, Design of cellular manufacturing systems for dynamic and uncertain production requirement with presence of routing flexibility. Ph.D. dissertation, Blacksburg State, University of Virginia (2000).
Tavakkoli–Moghaddam, R., Aryanezhad, M.B., Safaei, N. and Azaron, A., Solving a dynamic cell formation problem using metaheuristics. Appl. Math. Comput. 170 (2005) 761–780. Google Scholar
Saidi–Mehrabad, M. and Safaei, N., A new model of dynamic cell formation by a neural approach. Int. J. Adv. Manuf. Technol. 33 (2007) 1001–1009. Google Scholar
Tavakkoli–Moghaddam, R., Safaei, N. and Sassani, A., A new solution for a dynamic cell formation problem with alternative routing and machine costs using simulated annealing. J. Oper. Res. Soc. 59 (2008) 443–454. Google Scholar
Defersha, F. and Chen, M., A comprehensive mathematical model for the design of cellular manufacturing systems. Int. J. Prod. Econ. 103 (2006) 767–783. Google Scholar
Ahkioon, S., Bulgak, A.A. and Bektas, T., Cellular manufacturing systems design with routing flexibility, machine procurement, production planning and dynamic system reconfiguration. Int. J. Prod. Res. 47 (2009) 1573–1600. Google Scholar
Aryanezhad, M.B., Deljoo, V. and Mirzapour Al-e-hashem, S.M.J., Dynamic cell formation and the worker assignment problem: a new model. Int. J. Adv. Manuf. Technol. 41 (2009) 329–342. Google Scholar
Arkat, SM J. and Abbasi, B., Applying simulated annealing to cellular manufacturing system design. Int. J. Adv. Manuf. Technol. 32 (2007) 531–536. Google Scholar
Aljaber, N., Baek, W. and Chen, C.L., A tabu search approach to the cell formation problem. Comput. Int. Eng. 32 (1997) 169–185. Google Scholar
Spiliopoulos, K. and Sofianopoulou, S., Designing manufacturing cells: a staged approach and a tabu search algorithm. Int. J. Prod. Res. 41 (2003) 2531–2546. Google Scholar
Logendran, R. and Karim, Y., Design of manufacturing cells in the presence of alternative cell locations and material transporters. J. Oper. Res. Soc. 54 (2003) 1059–1075. Google Scholar
Wu, T.H., Low, C. and Wu, W.T., A tabu search approach to the cell formation problem. Int. J. Adv. Manuf. Technol. 23 (2004) 916–924. Google Scholar
Lei, D. and Wu, Z., Tabu search for multiple-criteria manufacturing cell design. Int. J. Adv. Manuf. Technol. 28 (2006) 950–956. Google Scholar
Yang, M.S. and Yang, J.H., Machine-part cell formation in group technology using a modified ART1 method. Eur. J. Oper. Res. 188 (2008) 140–152. Google Scholar
Venkumar, P. and Haq, A.N., Manufacturing cell formation using modified ART1 networks. Int. J. Adv. Manuf. Technol. 26 (2005) 909–916. Google Scholar
Solimanpur, M., Vrat, P. and Shankar, R., A multi-objective genetic algorithm approach to the design of cellular manufacturing systems. Int. J. Prod. Res. 42 (2004) 1419–1441. Google Scholar
Venugopal, V. and Narendran, T.T., A genetic algorithm approach to the machine component grouping problem with multiple objectives. Comput. Ind. Eng. 22 (1992) 469–480. Google Scholar
Pierreval, H., Caux, C., Pairs, J.L. and Viguier, F., Evolutionary approaches to the design and organization of manufacturing systems. Comput. Ind. Eng. 44 (2003) 339–364. Google Scholar
Defersha, F.M. and Chen, M., Machine cell formation using a mathematical model and a genetic-algorithm-based heuristic. Int. J. Prod. Res. 44 (2006) 2421–2444. Google Scholar
Wu, X., Chao–Hsien, C., Wang, Y., Yan, W., A genetic algorithm for cellular manufacturing design and layout. Eur. J. Oper. Res. 181 (2007) 156–167. Google Scholar
Yasuda, K., Hu, L., Yinza, Y., Grouping genetic algorithm for the multi-objective cell formation problem. Int. J. Prod. Res. 43 (2005) 829–853. Google Scholar
E. Atashpaz–Gargari and C. Lucas, Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. In IEEE Cong. Evolut. Comput. Singapore (2007) 4661–4667.
Sarayloo, F. and Tavakkoli–Moghaddam, R., Imperialistic Competitive Algorithm for Solving a Dynamic Cell Formation Problem with Production Planning. Adv. Intell. Comput. Theor. Appl. 6215 (2010) 266–276. Google Scholar
Onwubolu, G.C. and Mutingi, M., a genetic algorithm approach to cellular manufacturing systems. Comput. Ind. Eng. 39 (2001) 125–144. Google Scholar
E.G. Talbi, Metaheuristic from design to implementation. John Wiley & Sons Publisher: USA (2009).