Sequencing of parts on single-stage multifunctional machining systems using a chaos-embedded simulated annealing algorithm

International Journal of Production Research

Volumn 46, Issue 12, 2008, Pages 3387-3413

  Bachlaus, M ^a   Tiwari, M K ^a   Shankar, R ^b  

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

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

Flexible manufacturing system; Part sequencing; Re fixturing; Simulated annealing; Single stage multifunctional machining system (SSMS); Tool magazine replenishment

Indexed keywords

ECONOMIC ANALYSIS; EMBEDDED SYSTEMS; PROBLEM SOLVING; SIMULATED ANNEALING; STOCHASTIC MODELS;

SINGLE-STAGE MULTIFUNCTIONAL MACHINING SYSTEM (SSMS); TOOL MAGAZINE REPLENISHMENT;

CHAOTIC SYSTEMS;

EID: 42449108320     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207540600920876     Document Type: Article

References (30)

1. Aihara, K., Takabe, T. and Toyoda, M., Chaotic neural network. Phys. Lett. A, 1990, 144, 333-340.
2. Arena, P., Caponetto, R., Fortuna, L., Rizzo, A. and La Rosa, M., Self organization in non recurrent complex system. Int. J. Bifurcat. Chaos, 2000, 10(5), 1115-1125.
3. Caponetto, R., Fortuna, L., Fazzino, S. and Xibilia, M.G., Chaotic sequences to improve the performance of evolutionary algorithm. IEEE Trans. Evol. Comput., 2003, 7(3), 289-304.
4. Chakravarty, A.K. and Balakrishnan, N., Impact of job-sequence on the down-time of a deteriorating flexible machine. Eur. J. Oper. Res., 1995, 87(2), 299-315.
5. Chandra, P., Li, S. and Stan, M., Jobs and tool sequencing in an automated manufacturing environment. Int. J. Prod. Res., 1993, 31(12), 2911-2925.
6. Chen, L. and Aihara, K., Chaotic SA by a neural network model with transient chaos. New. Netw., 1995, 8, 915-930.
7. Chen, L. and Aihara, K., Global searching ability of chaotic neural networks. IEEE Trans. on Circuit Sys. I, 1999, 46, 974-993.
8. Chen, T. and Yang, L., Application of chaos in genetic algorithms. Comm. Theoret. Phys., 2002, 38, 168-172.
9. Crama, Y. and Oerlemans, A.G., A column approach to job grouping for flexible manufacturing systems. Eur. J. Oper. Res., 1994, 78, 58-80.
10. Determan, J. and Foster, A., Using chaos in genetic algorithm, in Proceedings of the 1999 Conference on Evolutionary Computation, 1999, Vol. 3, pp. 2094-2101 (IEEE Press: Piscataway, NJ).
11. Elert, G., The Chaos Hypertextbook - Mathematics in the Age of the Computer, 2005. Available online at: http://hypertextbook.com/chaos/
12. He, Y., Chaotic simulated annealing with decaying chaotic noise. IEEE Trans. New. Netw., 2002, 13(6), 1526-1531.
13. Hertz, A., Laporte, G., Mittaz, M. and Stecke, K.E., Heuristics for minimizing tool switches when scheduling part types on a flexible machine. IIE Trans., 1998, 30(8), 689-694.
14. Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P., Optimization by simulated annealing. Science, 1983, 220, 671-680.
15. Koo, P.H. and Tanchoco, J.M.A., Real-time operation and tool selection in single stage multifunctional machine systems. Int. J. Prod. Res., 1999, 37(5), 1023-1039.
16. Luo, C.Z. and Shen, H.H., Evolutionary algorithms with chaotic perturbations. Contr. Dec., 2000, 15, 557-560.
17. Manganaro, G. and Pineda de Gyvez, J., DNA computing based on chaos, in Proceedings of the IEEE International Conference on Evolutionary Computation, 1997 pp. 255-260, (IEEE Press: Piscataway, NJ).
18. Mingjun, J. and Huanwen, T., Application of chaos in simulated annealing. Chaos Solut. Fractals, 2004, 21, 933-941.
19. Nozawa, H., A neural network model as globally coupled map and application based on chaos. Chaos, 1992, 2, 377-386.
20. Parker, T.S. and Chua, L.O., Practical Numerical Algorithms for Chaotic System, 1989 (Springer: Berlin).
21. Peitgen, H., Jurgens, H. and Saupe, D., Chaos and Fractals, 1992 (Springer: Berlin).
22. Reinelt, G., TSPLIB - a traveling salesman problem library. ORSA J. Comput., 1991, 3, 376-384.
23. Sarma, S.E. and Wright, P.K., Algorithms for the minimization of setups and tool changes in simply fixturable components of milling. J. Manuf. Sys., 1996, 15(2), 95-111.
24. Singh, K.A., Mukherjee, A. and Tiwari, M.K., Incorporating kin selection in simulated annealing algorithm and its performance evaluation. Eur. J. Oper. Res., 2004, 158, 34-45.
25. Sinreich, D. and Nelkenbaum, D.B., Determining production sequences for single stage multifunctional machining systems based on the tradeoff between fixture cost, re-fixturing and tool replenishment. IIE Trans., 2005, 38(10), 813-828.
26. Sinreich, D., Rubinovitz, J., Milo, D. and Nakbily, G., Sequencing, scheduling and tooling single stage multifunctional machines in a small batch environment. IIE Trans., 2001, 33(10), 897-911.
27. Tang, C.S. and Denardo, E.V., Models arising from a flexible manufacturing machine, Part 1: Minimization of the number of tool switches. Oper. Res., 1988, 36, 767-777.
28. Tiwari, M.K., Sanjeev, K., Shashi, K., Prakash, and Shankar, R., Solving part type selection and operation allocation problems in an FMS: an approach using constraints based fast simulated annealing algorithm. IEEE Trans. Sys. Man Cybernet. A, 2006, 36(6), 1170-1184.
29. Wang, L. and Smith, K., On chaotic simulated annealing. IEEE Trans. Neur. Netw., 1998, 9, 716-718.
30. Yuan, X.H., Yuan, Y.B. and Zhang, Y.C., A hybrid chaotic genetic algorithm for short-term hydro system, scheduling. Math. Comput. Simul., 2002, 59, 319-327.