Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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A Multi-level Symbiotic Evolutionary Algorithm for FMS Loading Problems with Various Flexibilities

다양한 유연성을 갖는 FMS 부하할당 문제를 위한 다계층 공생 진화 알고리듬

  • Kim, Yeo Keun (Department of Industrial Engineering, Chonnam National University) ;
  • Kim, Jae Yun (Research Center for High-Quality Electric Components and Systems, Chonnam National University) ;
  • Lee, Won Kyun (Department of Industrial Engineering, Chonnam National University)
  • 김여근 (전남대학교 산업공학과) ;
  • 김재윤 (전남대학교 고품질전기전자부품 및 시스템연구센터) ;
  • 이원균 (전남대학교 산업공학과)
  • Published : 2003.03.31
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Abstract

This paper addresses FMS(Flexible Manufacturing System) loading problems with machine, tool and process flexibilities. When designing FMS planning, it is important to take account of these flexibilities for an efficient utilization of the resources. However, almost all the existing researches do not appropriately consider various flexibilities due to the problem complexity. This paper presents a new evolutionary algorithm to solve the FMS loading problems with machine, tool and process flexibilities. The algorithm is named a multi-level symbiotic evolutionary algorithm. The proposed algorithm is compared with the existing ones in terms of solution quality and convergence speed. The experimental results confirm the effectiveness of our approach.

Keywords

References

  1. Brandimarte, P. and Calderini, M. (1995), A hierarchical bicriterion approach to integrated process plan selection and job shop scheduling, International Journal of Production Research, 33, 161-181
  2. Bull, L.(1997), Evolutionary computing in multi-agent environments: partners, Proceedings 7th International on Conference Genetic Algorithms, East Lansing, MI, pp. 370-377
  3. Egbelu, P.J. and Kim, K.H.(1999), Scheduling in a production environment with multiple process plans per job, International Journal of Production Research, 37, 2725-2753
  4. Guerrero, F., Lozano, S., Koltai, T. and Larraneta, J.(1999), Machine loading and part type selection in flexible manufacturing systems, International Journal of' Production Research, 37, 1303-1317
  5. Ho, Y.C. and Moodie, C.L.(1996), Solving cell formation problems in a manufacturing environment with flexible processing and routing capabilities, International Journal of Production Research, 34, 2901-2923
  6. Kim, J.Y., Kim, YK., and Shin, T.H. (2000), Analysis of partnering strategies in symbiotic evolutionary algorithms, Journal of the Korean Operations Research and Management Science Society, 25,67-80
  7. Kim, J.Y., Kim, Y.H. and Kim, Y.K.(2001), An endosymbiotic evolutionary algorithm for optimization, Applied Intelligence, 15,117-130
  8. Kim, Y-D. (1993), A study on surrogate objectives for loading a certain type of flexible manufacturing systems, International journal of Production Research, 31, 381-392
  9. Kim, Y-D. (1993), A study on surrogate objectives for loading a certain type of flexible manufacturing systems, International journal of Production Research, 31, 381-392
  10. Kim, V-D. and Yano, C.A. (1993), A heuristic approach for loading problems in flexible manufacturing systems, IIE Transactions, 25,26-39
  11. Kim, Y.K. (2002), A set of data for the integration of process planning and scheduling in FMS, available at http://syslab.chonnam.ac.kr/linksl FMSdata-pp&s.doc
  12. Kim, Y.K., Park, K. and Ko, J. (2002), A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling, to appear in Computers & Operations Research
  13. Kuhn, H. (1995), A heuristic algorithm for the loading problem in flexible manufacturing systems, International journal of Flexible Manufacturing Systems, 7, 225-250
  14. Kumar, N. and Shanker, K. (2000), A genetic algorithm for FMS part type selection and machine loading, International journal of Production Research, 38, 3861-3887
  15. Lashkari, R.S., Dutta, S.P. and Padhye, A.M. (1987), A new formulation of operation assignment problem in flexible manufacturing systems, Management Science, 32, 1316-1335
  16. Lee, D-H and Kim, V-D. (1998), Iterative procedure for multi-period order selection and loading problems in flexible manufacturing systems, International journal of Production Research, 36, 2653-2668
  17. Lee, D-H and Kim, V-D. (2000), Loading algorithms for flexible manufacturing systems with partially grouped machines, IIE Transactions, 32, 33-47
  18. Lee, H.F. and Stecke, K.E. (1998), Production planning for flexible flow systems with limited machine flexibility, IIE Transactions, 30, 669-684
  19. Liang, M. and Dutta, S.P. (1993), An integrated approach to the part selection and machine loading problem in a class of flexible manufacturing systems. European journal of Operational Research, 67, 387-404
  20. Maher, M.L. and Poon, J. (1996), Modelling design exploration as co-evolution, Microcomputers in Civil Engineering, 11, 195-209
  21. Modi, B.K. and Shanker, K. (1994), Models and solution approaches for part movement minimization and load balancing in FMS with machine, tool and process plan flexibilities, International Journal of Production Research, 33, 1791-1816
  22. Nayak, G.K. and Acharya, D. (1998), Part type selection, machine loading and part type volume determination problem in FMS planning, International journal ol Production Research, 36, 1801-1824
  23. Potter, MA (1997), The design and analysis of a computational model of cooperative coevolution, Ph.D. dissertation, George Mason University
  24. Rachamadugu, R. and Stecke, K.E. (1994), Classification and review of FMS scheduling procedures, Production Planning and Control, 5, 2-20
  25. Stecke, K.E. (1983), Formulation and solution of nonlinear integer production planning problem for flexible manufacturing systems, Management sciences, 29, 273-288
  26. Steckc, K.E. and Raman N. (1995), FMS planning decisions, operating flexibilities, and system performance, IEEE Transactions on Engineering Management, 42, 82-90
  27. Syswerda, G. (1991), A study of reproduction in generational and steady-state genetic algorithms, foundations of Genetic Algorithms, San Mateo, CA, 94-101
  28. Tiwari, M.K. and Vidyarthi, N.K. (2000), Solving machine loading problems in a flexible manufacturing system using a genetic algorithm based heuristic approach, International journal of Production Research, 38, 3357-3384
  29. Vidyarthi, N.K. and Tiwari, M.K. (2001), Machine loading problems of FMS: a fuzzy-based heuristic approach, International Journal of Production Research, 39, 953-979
  30. Wilson, .J.M. (1989), An alternative formulation of the operation assignment problem in flexible manufacturing systems, International Journal of Production Research, 27, 1405-1412