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Parallel ant colonies for combinatorial optimization problems

  • El-ghazali Talbi
  • Olivier Roux
  • Cyril Fonlupt
  • Denis Robillard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1586)

Abstract

Ant Colonies (AC) optimization take inspiration from the behavior of real ant colonies to solve optimization problems. This paper presents a parallel model for ant colonies to solve the quadratic assignment problem (QAP). Parallelism demonstrates that cooperation between communicating agents improve the obtained results in solving the QAP. It demonstrates also that high-performance computing is feasible to solve large optimization problems.

Keywords

Local Search Tabu Search Combinatorial Optimization Problem Tabu List Quadratic Assignment Problem 
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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Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • El-ghazali Talbi
    • 1
  • Olivier Roux
    • 1
  • Cyril Fonlupt
    • 1
  • Denis Robillard
    • 2
  1. 1.LIFL URA-369 CNRSUniversité de Lille 1Villeneuve d’Ascq CedexFrance
  2. 2.LILUniversity of LittoralCalaisFrance

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