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Memetic Computing

, Volume 3, Issue 3, pp 199–216 | Cite as

Memetic cooperative models for the tool switching problem

  • Jhon Edgar Amaya
  • Carlos Cotta
  • Antonio J. Fernández-Leiva
Regular Research Papers

Abstract

This work deals with memetic-computing agent-models based on the cooperative integration of search agents endowed with (possibly different) optimization strategies, in particular memetic algorithms. As a proof-of-concept of the model, we deploy it on the tool switching problem (ToSP), a hard combinatorial optimization problem that arises in the area of flexible manufacturing. The ToSP has been tackled by different algorithmic methods ranging from exact to heuristic methods (including local search meta-heuristics, population-based techniques and hybrids thereof, i.e., memetic algorithms). Here we consider an ample number of instances of this cooperative memetic model, whose agents are adapted to cope with this problem. A detailed experimental analysis shows that the meta-models promoting the cooperation among memetic algorithms provide the best overall results compared with their constituent parts (i.e., memetic algorithms and local search approaches). In addition, a parameter sensitivity analysis of the meta-models is developed in order to understand the interplay among the elements of the proposed topologies.

Keywords

Memetic computing Memetic algorithm Local search Cooperation Tool switching problem 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Jhon Edgar Amaya
    • 1
  • Carlos Cotta
    • 2
  • Antonio J. Fernández-Leiva
    • 2
  1. 1.Laboratorio de Computación de Alto RendimientoUniversidad Nacional Experimental del TáchiraSan CristóbalVenezuela
  2. 2.Dept. Lenguajes y Ciencias de la Computación, ETSI InformáticaUniversity of MálagaMálagaSpain

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