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Selected Algorithmic Techniques for Parallel Optimization

In: Handbook of Combinatorial Optimization

Author

Listed:
  • Ricardo C. Corrêa

    (Universidade Federal do Rio de Janeiro, Núcleo de Computação Eletrônica)

  • Afonso Ferreira

    (CNRS-I3S-INRIA, SLOOP Project)

  • Stella C. S. Porto

    (Universidade Federal Fluminense, Computação Aplicada e Automação)

Abstract

The use of parallel algorithms for solving computationally hard problems becomes attractive as parallel systems, consisting of a collection of powerful processors, offer large computing power and memory storage capacity. Even though parallelism will not be able to overdue the assumed worst case exponential time or memory complexity of those problems (unless an exponential number of processors is used) [11], the average execution time of heuristic search algorithms which find good suboptimal solutions for many hard problems is polynomial. Consequently, parallel systems, possibly with hundreds or thousands of processors, give us the perspective of efficiently solving relatively large instances of hard problems.

Suggested Citation

  • Ricardo C. Corrêa & Afonso Ferreira & Stella C. S. Porto, 1998. "Selected Algorithmic Techniques for Parallel Optimization," Springer Books, in: Ding-Zhu Du & Panos M. Pardalos (ed.), Handbook of Combinatorial Optimization, pages 1879-1928, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-0303-9_29
    DOI: 10.1007/978-1-4613-0303-9_29
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