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Cooperative Coevolution in Inventory Control Optimisation

  • R. Eriksson
  • B. Olsson

Abstract

This paper introduces an extension to Potter and De Jong’s [5] work on cooperative coevolutionary GAs (CCGA). We discuss the problem of inventory control and discuss the potential advantages of applying an evolutionary method to this problem. We describe our approach and experimental design for solving the inventory control problem using a CCGA. We also show how the CCGA can be extended and modified in order to handle larger inventory control optimisation problems.

Keywords

Order Quantity Inventory Control Demand Rate Stock Level Customer Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    P.J. Angeline and J.B. Pollack. Competitive environments evolve better solutions for complex tasks. In Proceedings of ICGA-93, 1993.Google Scholar
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    P. Darwen and X. Yao. Automatic modularization by speciation. In Proceedings of ICEC’96, 1996.Google Scholar
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    R. Eriksson. Applying cooperative coevolution to inventory control parameter optimization. Master’s thesis, University of Skövde, Sweden, 1996.Google Scholar
  4. [4]
    W.D. Hillis. Co-evolving parasites improve simulated evolution as an optimization procedure. In Artificial Life II, 1992.Google Scholar
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    M.A. Potter and K.A. De Jong. A cooperative coevolutionary approach to function optimization. In Parallel Problem Solving from Nature 3, 1994.Google Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • R. Eriksson
    • 1
  • B. Olsson
    • 1
  1. 1.Department of Computer ScienceUniversity of SkövdeSweden

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