Abstract
This paper presents a simple algorithm for the job shop scheduling problem that combines the local search heuristic GRASP with a branch-and-bound exact method of integer programming. The proposed method is compared with similar approaches and leads to better results in terms of solution quality and computing times.
Keywords
- Schedule Problem
- Local Search
- Critical Path
- Critical Pair
- Iterate Local Search
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Adams, J., Balas, E., Zawack, D.: The Shifting Bottleneck Procedure for Job Shop Scheduling. Management Science 34(3), 391–401 (1988)
Aiex, R.M., Binato, S., Resende, M.G.C.: Parallel GRASP with path-relinking for job shop scheduling. Parallel Computing 29(4), 393–430 (2003)
Applegate, D., Cook, W.: A Computational Study of the Job-Shop Scheduling Problem. ORSA Journal on Computing 3(2), 149–156 (1991)
Balas, E., Vazacopoulos, A.: Guided Local Search with Shifting Bottleneck for Job Shop Scheduling. Management Science 44(2), 262–275 (1998)
Binato, S., Hery, W.J., Loewenstern, D.M., Resende, M.G.C.: A GRASP for Job Shop Scheduling. In: Ribeiro, C.C., Hansen, P. (eds.) Essays and surveys on metaheuristics, pp. 59–79. Kluwer Academic Publishers, Dordrecht (2001)
Carlier, J.: The one-machine sequencing problem. European Journal of Operational Research 11, 42–47 (1982)
Caseau, Y., Laburthe, F.: Disjunctive scheduling with task intervals. Technical Report LIENS, 95–25, Ecole Normale Superieure Paris (1995)
Chen, S., Talukdar, S., Sadeh, N.: Job-shop-scheduling by a team of asynchronous agentes. In: Proceedings of the IJCAI-93 Workshop on Knowledge-Based Production, Scheduling and Control, Chambery France (1993)
Danna, E., Rothberg, E., Pape, C.L.: Exploring relaxation induced neighborhoods to improve MIP solutions. Mathematical Programming, Ser. A. 102, 71–90 (2005)
Dell’Amico, M., Trubian, M.: Applying Tabu-Search to the Job-Shop Scheduling Problem (1993)
Denzinger, J., Offermann, T.: On Cooperation between Evolutionary Algorithms and other Search Paradigms. In: Proceedings of the 1999 Congress on Evolutionary Computational (1999)
Feo, T., Resende, M.: Greedy Randomized Adaptive Search Procedures. Journal of Global Optimization 6, 109–133 (1995)
Fernandes, S., Lourenço, H.R.: Optimized Search methods. Working paper, Universitat Pompeu Fabra, Barcelona, Spain (2006)
Fisher, H., Thompson, G.L.: Probabilistic learning combinations of local job-shop scheduling rules. In: Muth, J.F., Thompson, G.L. (eds.) Industrial Scheduling, pp. 225–251, Prentice Hall, Englewood Cliffs (1963)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completenes. Freeman, San Francisco (1979)
Jain, A.S., Meeran, S.: Deterministic job shop scheduling: Past, present and future. European Journal of Operational Research 133, 390–434 (1999)
Lawrence, S.: Resource Constrained Project Scheduling: an Experimental Investigation of Heuristic Scheduling techniques. Graduate School of Industrial Administration, Carnegie-Mellon University (1984)
Lourenço, H.R.: Job-shop scheduling: Computational study of local search and large-step optimization methods. European Journal of Operational Research 83, 347–367 (1995)
Lourenço, H.R., Zwijnenburg, M.: Combining large-step optimization with tabu-search: Application to the job-shop scheduling problem. In: Osman, I.H., Kelly, J.P. (eds.) Meta-heuristics: Theory & Applications, Kluwer Academic Publishers, Dordrecht (1996)
Nowicki, E., Smutnicki, C.: An Advanced Tabu Search Algorithm for the Job Shop Problem. Journal of Scheduling 8, 145–159 (2005)
Nowicki, E., Smutniki, C.: A Fast Taboo Search Algorithm for the Job Shop Problem. Management Science 42(6), 797–813 (1996)
Roy, B., Sussman, B.: Les probèms d’ordonnancement avec constraintes disjonctives. Note DS 9 bis, SEMA, Paris (1964)
Schrage, L.: Solving resource-constrained network problems by implicit enumeration: Non pre-emptive case. Operations Research 18, 263–278 (1970)
Storer, R.H., Wu, S.D., Vaccari, R.: New search spaces for sequencing problems with application to job shop scheduling. Management Science 38(10), 1495–1509 (1992)
Taillard, É.D. : Benchmarks for Basic Scheduling Problems. European Journal of Operational Research 64(2), 278–285 (1993)
Taillard, É.D.: Parallel Taboo Search Techniques for the Job Shop Scheduling Problem. ORSA Journal on Computing 6(2), 108–117 (1994)
Tamura, H., Hirahara, A., Hatono, I., Umano, M.: An approximate solution method for combinatorial optimisation. In: Transactions of the Society of Instrument and Control Engineers vol. 130, pp. 329–336 (1994)
Yamada, T., Nakano, R.: A genetic algorithm applicable to large-scale job-shop problems. In: Manner, R., Manderick, B. (eds.) Parallel Problem Solving from Nature, vol. 2, pp. 281–290. Elsevier Science, Amsterdam (1992)
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Fernandes, S., Lourenço, H.R. (2007). A GRASP and Branch-and-Bound Metaheuristic for the Job-Shop Scheduling. In: Cotta, C., van Hemert, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2007. Lecture Notes in Computer Science, vol 4446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71615-0_6
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DOI: https://doi.org/10.1007/978-3-540-71615-0_6
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