Using genetic algorithm to solve dynamic cell formation problem

Applied Mathematical Modelling

Volumn 34, Issue 4, 2010, Pages 1078-1092

  Deljoo, V ^a   Mirzapour Al e hashem, S M J ^b   Deljoo, F ^c   Aryanezhad, M B ^b  

^a BU ALI SINA UNIVERSITY   (Iran)

^b IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^c AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Dynamic cell formation; Genetic algorithm; Meta heuristics

Indexed keywords

CELL FORMATION; CLASSICAL OPTIMIZATION; COMPUTATIONAL TIME; DYNAMIC CELL FORMATION; DYNAMIC CONDITION; META HEURISTICS; NP-HARD PROBLEM; OPTIMAL SOLUTIONS;

CELLULAR MANUFACTURING; COMPUTATIONAL COMPLEXITY; COMPUTATIONAL EFFICIENCY; DISPERSION COMPENSATION; ERRORS; GENETIC ALGORITHMS; HEURISTIC METHODS;

PROBLEM SOLVING;

EID: 71849115347     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2009.07.019     Document Type: Article

References (29)

1. Fry T., Breen M., and Wilson M. A successful implementation of group technology and cell manufacturing. Prod. Invent. Manage. J. 28 3 (1987) 4-6
2. Collet S., and Spicer R. Improving productivity through cellular manufacturing. Prod. Invent. Manage. J. 36 1 (1995) 71-75
3. Levasseur G., Helms M., and Zink A. Conversion from a functional to the cellular manufacturing layout at Steward.inc. Prod. Inv. Manage. J. 36 3 (1995) 37-42
4. Singh N., and Rajamaani D. Cellular Manufacturing Systems: Planning and Control (1996), Chapman and Hall, New York
5. Onwubolu G.C., and Mutingi M. A genetic algorithm approach to cellular manufacturing systems. Comput. Ind. Eng. 39 (2001) 125-144
6. Xambre A.R., and Vilarinho P.M. A simulated annealing approach for manufacturing cell formation with multiple identical machines. Eur. J. Oper. Res. 151 (2003) 434-446
7. A. Mungwattana, Design of cellular manufacturing systems for dynamic and uncertain production requirement with presence of routing flexibility, Ph.D. Thesis, Blacksburg State University Virginia, 2000.
8. Seifoddini H. A probabilistic model for machine cell formation. J. Manuf. Syst. 9 1 (1990) 69-75
9. Harahalakis G., Nagi R., and Proth J. An efficient heuristic in manufacturing cell formation to group technology applications. Int. J. Prod. Res. 28 1 (1990) 185-198
10. Song S., and Hitomi K. Integrating the production planning and cellular, layout for flexible cell formation. Prod. Plan. Control 7 6 (1996) 585-593
11. Chen M. A mathematical programming model for systems reconfiguration in a dynamic cell formation condition. Ann. Oper. Res. 77 1 (1998) 109-128
12. E. Wicks, Designing cellular manufacturing systems with time varying product mixed and resource availability, Ph.D. Thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA, 1995.
13. Tavakkoli R., Aryanezhad M., Safaei N., and Azaron A. Solving a dynamic cell formation problem using met heuristics. Appl. Math. Comput. 170 (2005) 761-780
14. 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 (2006) 10.1016/j.ejor.2006.12.058
15. Defersha F., and Chen M. A comprehensive mathematical model for the design of cellular manufacturing systems. Int. J. Prod. Econ. 103 (2006) 767-783
16. Saidi-Mehrabad M., and Safaei N. A new model of dynamic cell formation by a neural approach. Int. J. Adv. Manuf. Technol. 33 9-10 (2007) 1001-1009
17. Bajestani M.A., Rabbani M., Rahimi-Vahed A.R., and Baharian Khoshkhou G. A multi-objective scatter search for a dynamic cell formation problem. Comput. Oper. Res. (2007) 10.1016/j.cor.2007.10.026
18. N. Safaei et al., A fuzzy programming approach for a cell formation problem with dynamic and uncertain conditions, Fuzzy Sets Syst. (2007), .
19. 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. (2007) 10.1080/00207540701581809
20. 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
21. 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. (2008) 10.1007/s00170-008-1479-4
22. Holland J.H. Adaptation in Natural and Artificial Systems (1975), University of Michigan Press, Ann Arbon
23. Goldberg D.E. Genetic Algorithm in Search Optimization, and Machine Learning (1989), Addison-Wesley, Massachusetts
24. J.D. Bagley, The behavior of adaptive systems which employ genetic and correlation algorithms, Ph.D. Thesis, University of Michigan, 1976.
25. R.S. Rosenberg, Simulation of genetic population with biochemical properties, Ph.D. Thesis, University of Michigan, 1967.
26. D.J. Cavicchio, Adaptive search using simulated evolution, Ph.D. Thesis, University of Michigan, 1972.
27. Gupta Y., Gupta M., Kumar A., and Sundram C. Minimizing total inter-cell and intra-cell moves in cell formation: a genetic algorithm. Int. J. Comput. Integr. Manuf. 8 2 (1995) 92-101
28. Joines J., Culberth C., and King R. Manufacturing cell design: an integer programming model employing genetic algorithms. IIE Trans. 28 1 (1996) 69-85
29. Venugopal V., and Narendran T. A genetic algorithm approach to the machine component grouping problem with multiple objectives. Comput. Ind. Eng. 22 4 (1992) 469-480