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Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization

  • Danny Munera
  • Daniel Diaz
  • Salvador Abreu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9595)

Abstract

Several real-life applications can be stated in terms of the Quadratic Assignment Problem. Finding an optimal assignment is computationally very difficult, for many useful instances. We address this problem using a local search technique, based on Extremal Optimization and present experimental evidence that this approach is competitive. Moreover, cooperative parallel versions of our solver improve performance so much that large and hard instances can be solved quickly.

Keywords

QAP Extremal optimization Heuristics Parallelism Cooperation 

Notes

Acknowledgments

The authors wish to acknowledge Stefan Boettcher (Emory University) for his explanations about the Extremal Optimization method. The experimentation used the cluster of the University of Évora, which was partly funded by grants ALENT-07-0262-FEDER-001872 and ALENT-07-0262-FEDER-001876.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of Paris 1-Sorbonne/CRIParisFrance
  2. 2.Universidade de Évora/LISPÉvoraPortugal

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