Abstract
Open Shop Scheduling is a meaningful paradigm of constraint satisfaction problems. In this paper, a method combining heuristic rules and evolutionary algorithms is proposed to solve this problem. Firstly, we consider several dispatching rules taken from literature that produce semi-optimal solutions in polinomial time. From these rules we have designed probabilistic algorithms to generate heuristic chromosomes that are inserted in the initial population of a conventional genetic algorithm. The experimental results show that the initial populations generated by the proposed method exhibits a high quality, in terms of both solutions cost and diversity. This way the genetic algorithm converges to much better solutions than when it starts from a ramdom population.
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References
Bierwirth, C.: A Generalized Permutation Approach to Jobshop Scheduling with Genetic Algorithms. OR Spectrum 17, 87–92 (1995)
Brucker, P., Hurink, J., Jurish, B., Wostmann, B.: A branch and bound algorithm for the open-shop problem. Discrete Applied Mathematics 76, 43–59 (1997)
Gonzales, T., Sahni, S.: Open shop scheduling to minimize finish time. Journal of the Association of Computing Machinery 23(4), 665–679 (1976)
Giffler, B., Thomson, G.L.: Algorithms for Solving Production Scheduling Problems. Operations Reseach 8, 487–503 (1960)
Guéret, C., Prins, C.: Classical and new heuristics for the open-shop problem: A computational study. European Journal of Operational Research 107, 306–314 (1998)
Liaw, C.-F.: An iterative improvement approach for the nonpreemtive open shop scheuling problem. European Journal of Operational Research 111, 509–517 (1998)
Liaw, C.-F.: A hybrid genetic algorithm for the open shop scheduling problem. European Journal of Operational Research 124, 28–52 (2000)
Pinedo, M.: Scheduling: Theory, Algorithms, and Systems. Prentice-Hall, Enblewoodd Cliffs (1995)
Taillard, E.: Bechmarks for basic scheduling problems. European Journal of Operational Research 64, 278–285 (1993)
Varela, R., Vela, C.R., Puente, J., Gómez, A.: A knowledge-based evolutionary strategy for scheduling problems with bottlenecks. European Journal of Operational Research 145, 57–71 (2003)
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© 2004 Springer-Verlag Berlin Heidelberg
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Puente, J., Díez, H.R., Varela, R., Vela, C.R., Hidalgo, L.P. (2004). Heuristic Rules and Genetic Algorithms for Open Shop Scheduling Problem. In: Conejo, R., Urretavizcaya, M., Pérez-de-la-Cruz, JL. (eds) Current Topics in Artificial Intelligence. TTIA 2003. Lecture Notes in Computer Science(), vol 3040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25945-9_39
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DOI: https://doi.org/10.1007/978-3-540-25945-9_39
Publisher Name: Springer, Berlin, Heidelberg
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