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A Grasp for Job Shop Scheduling

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Essays and Surveys in Metaheuristics

Part of the book series: Operations Research/Computer Science Interfaces Series ((ORCS,volume 15))

Abstract

In this paper, we describe a greedy randomized adaptive search procedure (GRASP) for the job shop scheduling problem (JSP). We incorporate to the conventional GRASP two new concepts: an intensification strategy and POP (Proximate Optimality Principle) in the construction phase. These two concepts were first proposed by Fleurent and Glover (1999) in the context of the quadratic assignment problem. Computational experience on a large set of standard test problems indicates that GRASP is a competitive algorithm for finding approximate solutions of the job shop scheduling problem.

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Author information

Authors and Affiliations

  1. CEPEL, Centro de Pesquisas de Energia Elétrica, P.O. Box 68007, Rio de Janeiro, 21944-970, Brazil

    S. Binato

  2. Bell Laboratories, Lucent Technologies, Whippanny, NJ, 07981, USA

    W. J. Hery

  3. Department of Computer Science, Rutgers University, Piscataway, NJ, 08855, USA

    D. M. Loewenstern

  4. Information Sciences Research Center, AT&T Labs Research, Florham Park, NJ, 07932, USA

    M. G. C. Resende

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  1. S. Binato
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  2. W. J. Hery
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  3. D. M. Loewenstern
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  4. M. G. C. Resende
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© 2002 Springer Science+Business Media New York

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Binato, S., Hery, W.J., Loewenstern, D.M., Resende, M.G.C. (2002). A Grasp for Job Shop Scheduling. In: Essays and Surveys in Metaheuristics. Operations Research/Computer Science Interfaces Series, vol 15. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1507-4_3

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  • DOI: https://doi.org/10.1007/978-1-4615-1507-4_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5588-5

  • Online ISBN: 978-1-4615-1507-4

  • eBook Packages: Springer Book Archive

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