Parallel Metaheuristics for Combinatorial Optimization (1999)
| Venue: | International School on Advanced Algorithmic Techniques for Parallel Computation with Applications |
| Citations: | 11 - 2 self |
BibTeX
@INPROCEEDINGS{Resende99parallelmetaheuristics,
author = {Mauricio G. C. Resende and Panos M. Pardalos and Sandra Duni Eksioglu and Sandra and Duni Eks¸io Glu},
title = {Parallel Metaheuristics for Combinatorial Optimization},
booktitle = {International School on Advanced Algorithmic Techniques for Parallel Computation with Applications},
year = {1999},
pages = {179--206},
publisher = {Kluwer Academic}
}
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Abstract
. In this paper, 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. 1. Introduction Search techniques are fundamental problem-solving methods in computer science and operations research. Search algorithms have been used to solve many classes of problems, including path-finding problems, two-player games, and constraint satisfaction problems. Classical examples of path-finding problems include many combinatorial optimization problems (e.g. integer programming) and puzzles (e.g. Rubic's cube, Eight Puzzle). Chess, backgammon, and Othello belong to the class of two player games, while a classic example of a constraint satisfaction problem is the eight-queens problem. In this paper, we focus on NP-hard combinator...
