Fuzzy job shop scheduling with lot-sizing

Annals of Operations Research

Volumn 159, Issue 1, 2008, Pages 275-292

  Petrovic, Sanja ^a   Fayad, Carole ^a   Petrovic, Dobrila ^b   Burke, Edmund ^a   Kendall, Graham ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b Institute for Clean Growth and Future Mobility   (United Kingdom)

Author keywords

Batching; Dispatching rules; Fuzzy multi objective genetic algorithm; Fuzzy rule based system; Job shop scheduling; Lot sizing; Real world application

Indexed keywords

EID: 38749112986     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1007/s10479-007-0287-9     Document Type: Article

References (35)

1. Adamopoulos, G. I., & Pappis, C. P. (1996). Fuzzy-linguistic approach to a multi-criteria sequencing problem. European Journal of Operational Research, 92(3), 628-636.
2. Agnetis, A., Alfieri, A., & Nicosia, G. (2004). A heuristic approach to batching and scheduling a single machine to minimise setup costs. Computers & Industrial Engineering, 46(2), 793-802.
3. Blazewicz, J., Domschke, W., & Pesch, E. (1996). The job shop scheduling problem: Conventional and new solution techniques. European Journal of Operational Research, 93, 1-33.
4. Dempster, M. A. H., Lenstra, J. K., & Rinnooy Kan, A. H. G. (Eds.). (1982). Deterministic and stochastic scheduling. Dordrecht: Reidel.
5. Drexl, A., & Kimms, A. (1997). Lot sizing and scheduling-Survey and extensions. European Journal of Operational Research, 99, 221-235.
6. Fargier, H. (1996). Fuzzy scheduling: Principles and experiments. In D. Dubois, H. Prade, & R. R. Yager (Eds.), Fuzzy information engineering, a guided tour of applications. New York: Wiley.
7. Fayad, C., & Petrovic, S. (2005). A genetic algorithm for the real world job-shop scheduling. In M. Ali & F. Esposito (Eds.), Lecture notes in artificial intelligence : Vol. 3533. Innovations in applied artificial intelligence (pp. 524-533). New York: Springer.
8. Goldberg, D. (1989). Genetic algorithms in search, optimisation, and machine learning. Reading: Addison-Wesley.
9. Han, S., Ishii, H., & Fuji, S. (1994). One machine scheduling problem with fuzzy due dates. European Journal of Operational Research, 79(1), 1-12.
10. Ishibuchi, H., Yamamoto, N., Misaki, S., & Tanaka, H. (1994). Local search algorithms for flow shop scheduling with fuzzy due-dates. International Journal of Production Economics, 33, 53-66.
11. Ishii, H., & Tada, M. (1995). Single machine scheduling problem with fuzzy precedence relation. European Journal of Operational Research, 87(2), 284-288.
12. Ishii, H., Tada, M., & Masuda, T. (1992). Two scheduling problems with fuzzy due-dates. Fuzzy Sets and Systems, 6(3), 336-347.
13. Karapapilidis, N., Pappis, C., & Adamopoulos, G. (2000). Fuzzy set approaches to lot sizing. In Scheduling under fuzziness (pp. 291-304). Heidelberg: Physica.
14. Klir, G., & Folger, T. (1998). Fuzzy sets, uncertainty and information. New Jersey: Prentice Hall.
15. Kuroda, M., & Wang, Z. (1996). Fuzzy job shop scheduling. International Journal of Production Economics, 44(1-2), 45-51.
16. Lee, Y. Y., Kramer, B. A., & Hwang, C. L. (1991). A comparative study of three lot-sizing methods for the case of fuzzy demand. International Journal of Operations and Production Management, 11(7), 72-80.
17. Leung, J. (Ed.). (2004). Handbook of scheduling: Algorithms, models, and performance analysis. New York: Chapman & Hall/CRC Press.
18. Li, Y., Luh, P. B., & Guan, X. (1994). Fuzzy optimization-based scheduling of identical machines with possible breakdown. In Proceedings-IEEE international conference on robotics and automation (pp. 3447-3452). San Diego, USA, May 1994.
19. Ouenniche, J., & Boctor, F. (1998). Sequencing, lot sizing and scheduling of several products in job shops: The common cycle approach. International Journal of Production Research, 36(4), 1125-1140.
20. Pedrycz, W., & Gowide, F. (1998). An introduction to fuzzy sets-analysis and design. Cambridge: MIT Press.
21. Petrovic, D. (1991). Decision support for improving systems reliability by redundancy. European Journal of Operational Research, 55, 357-367.
22. Pinedo, M. (2002). Scheduling: Theory, algorithms, and systems (2nd edn.) New Jersey: Prentice Hall.
23. Potts, C., & Kovalyov, M. (2000). Scheduling with batching: A review. European Journal of Operational Research, 120, 228-249.
24. Potts, C. N., & Van Wassenhove, L. N. (1995). Integrating scheduling with batching and lot-sizing: A review of algorithms and complexity. Journal of Operational Research Society, 43(5), 395-406.
25. Reeves, C. (1995a). Genetic algorithms. In V. J. Rayward-Smith (Ed.), Modern heuristic techniques for combinatorial problems (pp. 151-196). London: McGraw-Hill International.
26. Reeves, C. (1995b). A genetic algorithm for flowshop sequencing. Computers and Operations Research, 22(1), 5-13.
27. Ruspini, E. H., Bonissone, P., & Pedrycz, W. (Eds.). (1998). Handbook of fuzzy computation. Bristol: Institute of Physics Publishing (IOP).
28. Sakawa, M., & Kubota, R. (2000). Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms. European Journal of Operational Research, 120(2), 393-407.
29. Sarker, R., & Newton, C. (2002). A genetic algorithm for solving economic lot size scheduling problem. Computers & Industrial Engineering, 42, 189-198.
30. Sastry, K., Goldberg, D., & Kendall, G. (2005). Genetic algorithms. In E. K. Burke & G. Kendall (Eds.), Search methodologies: Introductory tutorials in optimization and decision support techniques (pp. 97-125). New York: Springer.
31. Slowinski, R., & Hapke, M. (Eds.). (2000). Scheduling under fuzziness. Heidelberg: Physica.
32. Tsujimura, Y., Park, S., Change, I. S., & Gen, M. (1993). An efficient method for solving flow shop problem with fuzzy processing times. Computer and Industrial Engineering, 25, 239-242.
33. Zadeh, L. A. (1965). Fuzzy sets. Information & Control, 8, 338-353.
34. Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management Science, 5, 89-96.
35. Wilson, R. H. (1934). A scientific routine for stock control. Harvard Business Review, 13, 116-128.