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Parallel Metaheuristics for Combinatorial Optimization

  • Sandra Duni Ekşiog̃lu
  • Panos M. Pardalos
  • Mauricio G. C. Resende
Part of the Applied Optimization book series (APOP, volume 67)

Abstract

In this chapter, we review parallel metaheuristics for approximating the global optimal solution of combinatorial optimization problems. Recent developments on parallel implementation of genetic algorithms, simulated annealing, tabu search, variable neighborhood search, and greedy randomized adaptive search procedures (GRASP) are discussed.

Keywords

Parallel local search parallel GRASP parallel genetic algorithms parallel simulated annealing parallel tabu search variable neighborhood descent parallel computing environments heuristics combinatorial optimization 

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Copyright information

© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  • Sandra Duni Ekşiog̃lu
    • 1
  • Panos M. Pardalos
    • 1
  • Mauricio G. C. Resende
    • 2
  1. 1.Center for Applied Optimization, Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.Information Sciences Research CenterAT&T Labs ResearchFlorham ParkUSA

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