Solving machine loading problem of FMS: An artificial intelligence (AI) based random search optimization approach

Handbook of Computational Intelligence in Manufacturing and Production Management

Volumn , Issue , 2007, Pages 19-43

  Prakash, Anoop ^a,b   Shankar, Ravi ^c   Shukla, Nagesh ^b,d   Tiwari, Manoj Kumar ^b,e  

^a UNIVERSITY OF CINCINNATI   (United States)

^b NATIONAL INSTITUTE OF FOUNDRY AND FORGE TECHNOLOGY   (India)

^c INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^d UNIVERSITY OF WARWICK   (United Kingdom)

^e INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 70449670727     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-582-5.ch002     Document Type: Chapter

References (71)

1. Ada, G.L., & Nossal, G.J.V. (1987). The clonal selection theory. Scientific American, 257, 50-57.
2. Anand, R.B., Tiwari, M.K., & Shankar, R. (2006). A self-organized neural network metamodelling and clonal selection optimization-based approach for the design of a manufacturing system. International Journal of Production Research, 44(6), 1147-1170.
3. Atmani, A., & Laskhari, R.S., (1998). A model of machine tool selection and operation alocation in FMS. International Journal of Production Research, 36(5), 1339-1349.
4. Bandyopadhyay, S., Murthy, C. A., & Pal, S. K. (1995). Pattern classification using genetic algorithms. Pattern Recognition Letters, 16, 801-808.
5. Bandyopadhyay, S., & Pal, S. K. (1998). Incorporating chromosome differentiation in genetic algorithms. Information Science, 104, 293-319.
6. Bell, J.E., & McMullen, P.R. (2004). Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Informatics, 18, 41-48.
7. Berrada, M., & Stecke, K. (1983). A branch and bound approach for machine loading in flexible manufacturing system (Working Paper No. 329). Ann Arbor, MI: Division of Research Graduates School of Business Administration, University of Michigan.
8. Chen, Y.J., & Askin, R.G. (1990). A multiobjective evaluation of flexible manufacturing system loading heuristics. International Journal of Production Research, 28, 895-911.
9. Chen, I.J., & Chung, C.H. (1996). An examination of flexibility measurements and performance of flexible manufacturing systems. International Journal of Production Research, 34(2), 379-394.
10. Clevland, G. A., & Smith, S. F. (1989). Using genetic algorithms to scheduling flow shop releases. In Proceedings of the Third International Conference on Genetic Algorithm and Their Applications Palo Alto, California (pp. 160-169). Morgan Kaufmann.
11. Cox, L. A., Davis, L., & Qiu, Y. (1991). Dynamic anticipatory routing in circuit-switched telecommunications networks. Handbook of genetic algorithms. New York: Van Nostrand Reinhold.
12. Dasgupta, D. (1999). An overview of artificial immune systems and their applications. In D. Dasgupta (Ed.), Artificial immune systems and their applications. Berlin: Springer.
13. Davis, L. (1985a). Job shop scheduling with genetic algorithms. In Proceedings of the International Conference on Genetic Algorithms and Their Applications, Carnegie Mellon University, Pittsburgh, Pennsylvania (pp. 136-140).
14. Davis, L. (1985b). Applying adaptive algorithms to epistatic domains. Proceedings of the International Joint Conference on Artificial Intelligence (pp. 162-164).
15. Davis, L. (1991). Handbook of genetic algorithms. New York: VanNostrand Reinhold.
16. De Castro, L.N., & Von Zuben, F.J. (2000). The clonal selection algorithm with engineering applications. In Proceedings of Genetic and Evolutionary Computation Conference, Workshop on Artificial Immune Systems and Their Applications, Las Vegas (pp. 36-37).
17. Dorigo, M., Caro, G.D., & Gambardella, L.M. (1997). Ant colony system: A cooperative learning approach to the travelling salesman problem. IEEE Transactions on Evolutionary Computation, 1(1), 53-66.
18. Dorigo, M., & Di Caro, G. (1999). The ant colony optimization meta-heuristic. In D. Corne, M. Dorigo, & G. Glover (Eds.), New ideas in optimization (pp. 11-32).
19. Endoh, S., Toma, N., & Yamada, K. (1998). Immune algorithm for n-TSP. In Proceedings of the 1998 IEEE International Conference on Systems Man and Cybernetics, San Diego, California (pp. 3844-3849).
20. Fourmann, M.P. (1985). Comparison of symbolic layout using genetic algorithm. In Proceedings of the First International Conference on Genetic Algorithms and their Applications (pp. 141-155). Hillsdale, NJ: Lawrence Erlbaum Associate.
21. Gaspar, A., & Collard, P. (2000). Two models of immunization for time dependent optimization. In Proceeding of the 2000 IEEE International Conference on Systems, Man, and Cybernetics, Nashville (pp. 113-118).
22. Glover, F. (1990). Tabu search: A tutorial. Interfaces, 20(4), 74-94.
23. Goldberg, D.E. (1987a). Computer aided gas pipeline operation using genetic algorithms and rule learning, Part 1: Genetic algorithms in pipeline optimization. Engineering with Computers, 3(1) 35-45.
24. Goldberg, D.E. (1987b). Computer aided gas pipeline operation using genetic algorithms and rule learning, Part 2: Rule learning control of a pipeline under normal and abnormal conditions. Engineering with Computers, 3(1) 47-58.
25. Goldberg, D.E. (1989). Genetic algorithms in search, optimization and machine learning. Reading, MA: Addison-Wesley.
26. Goldberg, D.E., Korb, B., & Deb, K. (1989). Messy genetic algorithm: Motivation analysis and first results. Complex System. Complex System Publications, 493-530.
27. Grefenstette, J. J., Gopal, R., Rormatia, B., & Vangucht, D. (1985). Genetic algorithms for travelling salesman problem In Proceedings of the First International Conference on Genetic Algorithms and their Applications. Hillsdale, NJ: Lawrence Erlbaum Associates.
28. Guerreore, F., Lozano, S., Koltai, T., & Larraneta, J. (1999). Machine loading and part type selection in flexible manufacturing system. International Journal of Production Research, 37(6), 1303-1317.
29. Gupta, M., Gupta, Y., Kumar, A., & Sundram, C. (1996). A genetic algorithm-based approach to cell composition and layout design problems. International Journal of Production Research, 34(2), 447-482.
30. Holland, H.H. (1975). Adaptation in natural and artificial systems. Detroit: University of Michigan Press.
31. Hwang, S.S. (1986). Models for production planning in flexible manufacturing system. Unpublished doctoral thesis, University of California, Berkley.
32. Jerne, N.K. (1974). Towards a network theory of the immune system. Annual Immunology (Inst. Pasteur), 125C, 373-389.
33. Kim, J.Y., & Kim, Y.K. (2005). Multileveled symbiotic evolutionary algorithm: Application to FMS loading problems. Artificial Intelligence, 22, 233-249.
34. Kim, Y.D., & Yano, C.M. (1994). A new branch and bound algorithm for loading problems in flexible manufacturing systems. International journal of flexible manufacturing systems, 6, 361-382.
35. Kirkpatrick, F., Gelatte, C.D., & Vecchi, M.P. (Eds.). (1983). Optimization by simulated annealing. Science, 220(4598), 671-680.
36. Kumar, A., Prakash, A., Tiwari, M.K., Shankar, R., & Baveja, A. (2006). Solving machine-loading problem of a flexible manufacturing system with constraint-based genetic algorithm. European Journal of Operational Research, 175(2), 1043-1069.
37. Kumar, N., & Shanker, K. (2000). A genetic algorithm for FMS part type selection and machine loading. International Journal of Production Research, 16(38), 3861-3887.
38. Kumar, P., Singh, N., & Tiwari, N.K. (1990). Multicriteria analysis of the loading problem in flexible manufacturing system using max-min approach. International Journal of Production Research, 2(2), 13-23.
39. Kusiak, A. (1985). Flexible manufacturing systems: A structural approach. International Journal of Production Research, 23(6), 1057-1073.
40. Lashkari, R.S., Dutta, S.P., & Padhye, A.M. (1987). A new formulation of operation allocation problem in flexible 1258 manufacturing systems: mathematical modeling and computational experience. International Journal of Production Research, 25(9), 1267-1287.
41. Lee, C.Y., Piramuthu, S., & Tsai, Y.K. (1997). Job shop scheduling with genetic algorithm and machine learning. International Journal of Production Research, 35(4), 1171-1191.
42. Liang, M., & Dutta, S.P. (1993). An integrated approach to part- selection and machine-loading problem in class of flexible manufacturing systems. European Journal of Operational Research, 67(3), 387-404.
43. Maniezzo, V., Colorni, A., & Dorigo, M. (1999). The ant system applied to the quadratic assignment problem. IEEE Transactions on Knowledge and Data Engg, 11(50), 769-778.
44. Maniezzo, V., Dorigo, M., & Colorni, A. (1996). Ant system: Optimization by a colony of cooperating agents. IEEE Transaction on Systems, Man and Cybernatics, 26(1), 29-41.
45. Michaelwicz, Z. (1992). Genetic algorithm + data structure = evaluation programs. New York: Springer Verlag.
46. Mukopadhyay, S.K., Midha, S., & Krishna, V.A. (1992). A heuristic procedure for loading problem in flexible manufacturing system. International journal of production research, 30(9), 2213-2228.
47. Mukhopadhyay, S.K., Singh, M.K., & Srivastava, R. (1998). FMS loading: A simulated annealing approach. International Journal of Production Research, 36(6), 1629-1647.
48. Nayak, G.K., & Acharya, D. (1998). Part type selection and machine-loading and part type volume determination problem in FMS planning. International Journal of Production Research, 36, 1801-1824.
49. Nossal, G.J.V. (1994). Negative selection of lymphocytes. Cell, 76, 229-239.
50. Prakash, A., Khilwani, N., Tiwari, M.K., & Cohen, Y. (in press). Modified immune algorithm for job selection and operation allocation problem in flexible manufacturing system. Advances in Engineering Software.
51. Rai, R., Kameshwaran, S., & Tiwari, M.K. (2002). Machine-tool selection and operation allocation in FMS: Solving a fuzzy goal-programming model using a genetic algorithm. International Journal of Production Research, 40(3), 241-265.
52. Ram, B., Sarin, S., & Chen, C.S. (1990). A model and solution approach for the machine loading and tool allocation problem in FMS. International Journal of Production Research, 28(4), 637-645.
53. Sarin, S.C., & Chen, C.S. (1987). The machine loading and tool allocation problem in a flexible manufacturing system. International Journal of Production Research, 25(7), 1081-1094.
54. Sarma, U.M.B.S., Kant, S., Rai, R., & Tiwari, M.K. (2002). Modeling the machine loading problem of FMSs and its solution using a tabu-search-based heuristic. International Journal of Computer Integrated Manufacturing, 15(4), 285-295.
55. Sawik, T. (1990). Modeling and scheduling of flexible manufacturing systems. European Journal of Operational Research, 45(2-3), 177-190.
56. Shanker, K., & Srinivasulu, A. (1989). Some solution methodologies for a loading problem in random FMS. International Journal of Production Research, 27(6), 1019-1034.
57. Shanker, K., & Tzen, Y.J. (1985). A loading and dispatching problem in a random flexible manufacturing system. International Journal of Production Research, 16(5), 383-393.
58. Singhal, K. (1978). Integrating production decisions. International Journal of Production Research, 16(5), 383-393.
59. Stecke, K. (1983). Formulation and solution of non-linear integer production planning problems for flexible manufacturing system. Management Sciences, 29, 272-288.
60. Stecke, K.E. (1986). A hierarchical approach to solving grouping and loading problems of flexible manufacturing systems. European Journal of Operational Research, 24(3), 369-378.
61. Stecke, K.E. (1993). Planning and scheduling approaches to operate a particular FMS. European Journal of Operational Research, 61(3), 273-291.
62. Stecke, K., & Solberg, J. (1981). Loading and control policies for a flexible manufacturing system. International Journal of Production Research, 19, 481-490.
63. Stuetzle, T., & Hoos, H.H. (2000). Max-min ant system. Future Generation Computer Systems, 16, 889-914.
64. Szumlanski, S.R., Wu, A.S., & Hughes, C.E. (2006, July 16-20). Conflict resolution and a framework for collaborative interactive evolution. American Association for Artificial Intelligence (AAAI). Boston.
65. Taillerd, E. (1990). Some efficient heuristic methods for flow shop sequencing problems. European Journal of Operational Research, 47, 65-74.
66. Tiwari, M.K., Hazarika, B., Vidyarthi, N.K., Jaggi, P., & Mukopadhyay, S.K. (1997). A heuristic solution approach to the machine loading problem of FMS and its petri net model. International Journal of Production Research, 35(8), 2269-2284.
67. Tiwari, M.K., Kumar, S., Kumar S., Prakash, A., & Shankar, R. (2006). Solving part type selection and operation allocation problems in a FMS: An approach using consraint based fast simulated annealing algorithm. IEEE Transaction on Systems, Man, and Cybernatics Part-A, 36(6), 1170-1184.
68. Tiwari, M.K., & Swarnkar, R. (2004). Modeling machine loading problem of FMSs and its solution methodology using a hybrid tabu search and simulated annealing-based heuristic approach. Robotics and Computer-Integrated Manufacturing, 20, 199-209.
69. Tiwari, M.K., & 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(14), 3357-3384.
70. Van Looveren, A.J., Gelders, J.L.F., & Van Wassenhove, L.N. (1986). A review of FMS planning models. In A. Kusiak (Ed.), Modeling and design of flexible manufacturing systems (pp. 3-31). Amsterdam: Elsevier.
71. Whitney, C.K., & Gaul, T.S. (1984). Sequential decision procedure for batching and balancing in FMSs. In Proceedings of the First ORSA/TIMS Conference on FMS (pp. 243-248). University of Michigan.