Abstract
In this work we present a genetic algorithm for the job shop problem with recirculation. The genetic algorithm includes a local search procedure that is implemented as a genetic operator. This strategy differs from the memetic algorithm because it is not guaranteed that the local minimum is achieved in each iteration.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Aiex, R.M., Binato, S., and Resende, M.G.C. (2003),“Parallel GRASP with path-relinking for job shop scheduling,” Parallel Computing, vol. 29, pp. 393–430.
Aydin, E., and Fogarty, T.C. (2002),“Modular simulated annealing for job shop scheduling running on distributed resource machine (DRM),” Technical Report, South Bank University, London, (Downloadable from website http://www.dcs.napier.ac.uk/~benp/dream/dreampaperl3.pdf).
Beasley, J.E. (1990),“OR-Library: distributing test problems by electronic mail,” Journal of the Operational Research Society, vol. 41, pp. 1069–1072. (website http://mscmga.ms.ic.ac.uk/info.html).
Binato, S., Hery, W.J., Loewenstern, D.M., and Resende, M.G.C. (2001),“A GRASP for job shop scheduling, in: C.C. Ribeiro, P. Hansen, (Eds.), Essays and Surveys in Metaheuristics, Kluwer Academic Publishers, Dordrecht, pp. 58–79.
Brucker, P. and Knust, S. (2003), Complexity results for scheduling problems, Department of Mathematics/Computer Science, University of Osnabrück, (Downloadable from website http://www.mathematik.uniosnabrueck.de/research/OR/class/).
French, S. (1982), Sequencing and Scheduling – An Introduction to the Mathematics of the Job-Shop, Ellis Horwood Limited, Chicester.
Garey, M., Johnson, D.S., and Sethi, R. (1976),“The complexity of flowshop and jobshop scheduling,” Mathematics of Operation Research, vol. 1, pp. 117–129.
Giffler, B. and Thompson, G.L. (1960),“Algorithms for solving production scheduling problems,” Operations Research, vol. 8, pp. 487–503.
Goldberg, D.E. (1989) Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA.
Gonçalves, J.F. and Beirão, N.C. (1999),“Urn algoritmo genético baseado em chaves aleatórias para sequenciamento de operações,” Revista Associação Portuguesa de Desenvolvimento e Investigaçõo Operacional, vol. 19, pp. 123–137.
Gonçalves, J.F., Mendes, J.J.M., and Resende, M.G.C. (2002),“A hybrid genetic algorithm for the job shop scheduling problem,” AT&T Labs Research Technical Report TD-5EAL6J, Florham Park, NJ, (Downloadable from website http://www.research.att.com/~mgcr/doc/hgajss.pdf).
Jain, A.S. and Meeran, S. (1999),“A state-of-the-art review of job-shop scheduling techniques,” European Journal of Operations Research, vol. 113, pp. 390–434.
Kolonko, M. (1999),“Some new results on simulated annealing applied to the job shop scheduling problem,” European Journal of Operational Research, vol. 113, pp. 123–136.
Lenstra, J.K. and Rinnooy Kan, A.H.G. (1979),“Computational complexity of discrete optimization problems,” Annals of Discrete Mathematics, vol. 4, pp. 121–140.
Nowicki, E. and Smutnicki, C. (1996),“A fast taboo search algorithm for the job-shop problem,” Management Science, vol. 42, pp. 797–813.
Oliveira, J.A. (2001), Aplicação de Modelos e Algoritmos de Investigação Operacional ao Planeamento de Operações em Armazéns, Ph.D. Thesis, Universidade do Minho, Braga.
Ono, I., Yamamura, M., and Kobayashi, S. (1996),“A genetic algorithm for job-shop scheduling problems using job-based order crossover,” Proceedings of ICE′96, pp. 547–552.
Roy, B. and Sussmann, B. (1964),“Les Problemes D’Ordonnancement Avec
Vaessens, R.J.M., Aarts, E.H.L., and Lenstra, J.K. (1996),“Job Shop Scheduling by local search,” INFORMS Journal on Computing, vol. 8, pp. 302–317. (Downloadable from web site http://joc.pubs.informs.org/BackIssues/Vol008/ Vol008No03Paper09.pdf).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer
About this paper
Cite this paper
Oliveira, J.A. (2006). A Genetic Algorithm with a Quasi-local Search for the Job Shop Problem with Recirculation. In: Abraham, A., de Baets, B., Köppen, M., Nickolay, B. (eds) Applied Soft Computing Technologies: The Challenge of Complexity. Advances in Soft Computing, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31662-0_18
Download citation
DOI: https://doi.org/10.1007/3-540-31662-0_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31649-7
Online ISBN: 978-3-540-31662-6
eBook Packages: EngineeringEngineering (R0)