Incorporating Tabu Search Principles into ACO Algorithms

  • Franco Arito
  • Guillermo Leguizamón
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5818)

Abstract

ACO algorithms iteratively build solutions to an optimization problem. The solution construction process is guided by pheromone trails which represents a mechanism of adaptation that allows to bias the sampling of new solutions toward promising regions of the search space. Additionally, the bias of the search is influenced by problem dependent heuristic information. In this work we describe an ACO algorithm that incorporates principles of Tabu Search (TS) for the solution construction process. These concepts specifically address the way that TS uses the history of the search to avoid visiting solutions already analyzed. We consider the Quadratic Assignment Problem (QAP) as a case-study, since this problem was also tackled in a closely related research to ours, the one on the usage of external memory in ACO algorithms. The performance of the proposed algorithm is assessed by considering a well-known set of instances of QAP.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Franco Arito
    • 1
  • Guillermo Leguizamón
    • 1
  1. 1.Laboratorio de Investigación y Desarrollo en Inteligencia Computacional, Departamento de Informática, Facultad de Ciencias Físico Matemáticas y NaturalesUniversidad Nacional de San LuisSan LuisArgentina

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