Abstract
The flow-shop scheduling problem is one of the most well-known problems in the area of scheduling. The objective of minimising the makespan is often employed as a criterion for flow shop scheduling since Johnson’s work on the subject. The problem is strongly NP-hard and therefore many approximation algorithms have been developed to provide a good solution in reasonable run times. In this research, a mechanism that records the good solution’s characteristics is designed and introduced into simulated annealing to make the searching procedure more robust. Computational experiments show that simulated annealing with a designed mechanism can make the solution quality more robust than it is without the mechanism. In addition, the proposed simulated annealing procedure is also compared with some previously published algorithms in regard to performance. Results show that the proposed simulated annealing procedure performs well with respect to solution and efficiency.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Johnson SM (1954) Optimal two-and three-stage production schedules with setup times included. Nav Res Log 1:61–68
Ignall E, Schrage LE (1965) Application of branch-and-bound techniques to some flow shop problems. Operat Res 13:400–412
Lomnicki Z (1965) A branch-and-bound for the exact solution of the three machine scheduling problem. Operat Res 16:89–107
Palmer DS (1965) Sequencing jobs through a multi-stage process in the minimum total time—a quick method of obtaining a near optimum. Operat Res 16:101–107
Campbell HG, Dudek RA, Smith ML (1970) A heuristic algorithm for the n-job, m-machine sequencing problem. Manag Sci 16/B:630–637
Nawaz M, Enscore EE, Ham I (1983) A heuristic algorithm for m-machine, n-job flowshop sequencing problem. Omega 11:91–98
Koulamas C (1998) A new constructive heuristic for the flowshop scheduling problem. Eur J Oper 105:66–71
Ishibuchi H, Misaki S, Tanaka H (1995) Modified simulated annealing algorithms for the flow shop sequencing problem. Eur J Oper 81:388–398
Osman IH, Potts CN (1989) Simulated annealing for permutation flow-shop scheduling, Omega 17:551–557
Ogbu FA, Smith DK (1990) The application of the simulated annealing algorithm to the solution of the n/m/C max flow shop problem, Computer and Operat Res 17:243–253
Taillard E (1990) Some efficient heuristic methods for the flow shop scheduling problems. Eur J Oper 47:65–74
Nowicki E, Smutnicki C (1996) A fast tabu search algorithm for the permutation flow-shop problem. Eur J Oper 91:160–175
Ben-Daya M, Al-Fawzan M (1998) A tabu search approach for the flow shop scheduling problem. Eur J Oper 109:88–95
Chen C-L, Vempati SV, Aljaber N (1995) An application of genetic algorithms for flow shop problems. Eur J Oper 80:389–396
Reeves C (1995) A genetic algorithm for flow shop sequencing. Comput Oper Res 22:5–13
Murata T, Ishibuchi H, Tanaka H (1996) Genetic algorithms for the flowshop scheduling problems. Comput Ind Eng 30:1061–1071
Van Laarhoven PJM, Aarts EHL, Lenstra JK (1992) Job shop scheduling by simulated annealing. Operat Res 40:113–125
Low C, Wu T-H (2001) Mathematical modeling and heuristic approaches to operation scheduling problems in an FMS environment. Int J Prod Res 39:689–708
Taillard E (1993) Benchmarks for the basic scheduling problems. Eur J Oper 64:278–285
Demirkol E, Mehta S, Uzsoy R (1998) Benchmarks for shop scheduling problems. Eur J Oper 109:137–141
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Low, C., Yeh, JY. & Huang, KI. A robust simulated annealing heuristic for flow shop scheduling problems. Int J Adv Manuf Technol 23, 762–767 (2004). https://doi.org/10.1007/s00170-003-1687-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-003-1687-x