Parallelized Heuristics for Combinatorial Search

  • K. Holmqvist
  • A. Migdalas
  • P. M. Pardalos
Chapter
Part of the Applied Optimization book series (APOP, volume 7)

Abstract

Combinatorial optimization problems of various kinds arise in different fields. Many of these problems are large, complicated problems that require huge computing powers and long execution times for the solving procedure. Therefore the use of massively parallel computer architectures presents an interesting opportunity. The difficulty in solving these problems can sometimes also necessitate the use of heuristic methods that do not necessarily find the global optimum. In this chapter, we give brief descriptions of the techniques and discuss different parallel implementations of the modern heuristic techniques Simulated Annealing, Tabu Search, Genetic Algorithms, and GRASP.

Keywords

Heuristics Simulated Annealing Tabu Search Genetic Algorithms GRASP Combinatorial Optimization parallel algorithms 
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Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • K. Holmqvist
  • A. Migdalas
  • P. M. Pardalos

There are no affiliations available

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