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Lot-Sizing in a Foundry Using Genetic Algorithm and Repair Functions

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Evolutionary Computation in Combinatorial Optimization (EvoCOP 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3448))

Abstract

The paper presents a study of genetic algorithms applied to a lot-sizing problem, which has been formulated for an operational production planning in a foundry. Three variants of genetic algorithm are considered, each of them using special crossover and mutation operators as well as repair functions. The real size test problems, based on the data taken from the production control system, are presented for assessment of the proposed algorithms. The obtained results show that the genetic algorithm with two repair functions can generate good suboptimal solutions in the time, which can be acceptable from the decision maker point of view.

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Authors and Affiliations

  1. Faculty of Management, Dept. of Applied Computer Science, AGH University of Science and Technology, ul. Gramatyka 10, 30-067, Kraków, Poland

    Jerzy Duda

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  1. Jerzy Duda
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Editors and Affiliations

  1. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9–11/1861, 1040, Vienna, Austria

    Günther R. Raidl

  2. SAP AG, Neurottstr. 16, P.O. Box, Walldorf, Germany

    Jens Gottlieb

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© 2005 Springer-Verlag Berlin Heidelberg

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Duda, J. (2005). Lot-Sizing in a Foundry Using Genetic Algorithm and Repair Functions. In: Raidl, G.R., Gottlieb, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2005. Lecture Notes in Computer Science, vol 3448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31996-2_10

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  • DOI: https://doi.org/10.1007/978-3-540-31996-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25337-2

  • Online ISBN: 978-3-540-31996-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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