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A Genetic Algorithm for the Job Shop on an ASRS Warehouse

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Book cover Computational Science and Its Applications – ICCSA 2012 (ICCSA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7335))

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Abstract

This paper describes the application of a metaheuristic to a real problem that arises within the domain of loads’ dispatch inside an automatic warehouse. The truck load operations on an automated storage and retrieval system warehouse could be modeled as a job shop scheduling problem with recirculation. The genetic algorithm is based on random key representation, that is very easy to implement and it allows the use of conventional genetic operators for combinatorial optimization problems. This genetic algorithm includes specific knowledge of the problem to improve its efficiency. A constructive algorithm based in Giffler-Thompson’s algorithm is used to generate non delay plans. The constructive algorithm reads the chromosome and decides which operation is scheduled next. This option increases the efficiency of the genetic algorithm. The algorithm was tested using some instances of the real problem and computational results are presented.

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Author information

Authors and Affiliations

  1. Centre ALGORITMI, University of Minho, 4700-057, Braga, Portugal

    José Figueiredo, José A. Oliveira, Luis Dias & Guilherme A. B. Pereira

Authors
  1. José Figueiredo
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  2. José A. Oliveira
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  3. Luis Dias
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  4. Guilherme A. B. Pereira
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Editor information

Editors and Affiliations

  1. Laboratory of Urban and Territorial Systems, University of Basilicata, 10, Viale dell’Ateneo Lucano, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli 1, 06123, Perugia, Italy

    Osvaldo Gervasi

  3. Department of Cyber Security Science, Federal University of Technology, Gidan Kwano Campus, Minna, Nigeria

    Sanjay Misra

  4. Faculty of Engineering, Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Rua Sao Francisco Xavier, 524, 50. andar, sala 5145-F, Maracana, 20.550-013, Rio de Janeiro, RJ, Brazil

    Nadia Nedjah

  5. Department of Production and Systems, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  6. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

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© 2012 Springer-Verlag Berlin Heidelberg

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Figueiredo, J., Oliveira, J.A., Dias, L., Pereira, G.A.B. (2012). A Genetic Algorithm for the Job Shop on an ASRS Warehouse. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31137-6_10

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  • DOI: https://doi.org/10.1007/978-3-642-31137-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31136-9

  • Online ISBN: 978-3-642-31137-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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