Selected Algorithmic Techniques for Parallel Optimization

Ricardo C. Corrêa (), Afonso Ferreira () and Stella C. S. Porto ()
Additional contact information
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

A chapter in Handbook of Combinatorial Optimization, 1998, pp 1879-1928 from Springer

Abstract: 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.

Keywords: Genetic Algorithm; Quadratic Assignment Problem; Discrete Optimization Problem; Algorithmic Technique; Good Speedup (search for similar items in EconPapers)
Date: 1998
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-0303-9_29

Ordering information: This item can be ordered from
http://www.springer.com/9781461303039

DOI: 10.1007/978-1-4613-0303-9_29

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().