DocumentCode :
1538400
Title :
Nature´s algorithms [genetic algorithms]
Author :
Carnahan, Joseph ; Sinha, Roopak
Author_Institution :
Naval Surface Warfare Center, Dahlgren, VA, USA
Volume :
20
Issue :
2
fYear :
2001
Firstpage :
21
Lastpage :
24
Abstract :
Combinatorial optimization problems typically require every possible solution to be evaluated to ensure finding the optimal solution. Since such exhaustive searches are often impractical, there is now a vast body of heuristic algorithms for them. Among the algorithms are those based on metaphors borrowed from other areas of science. The idea is that key elements of physical processes can be used abstractly to form the basis of an optimization algorithm. This article presents a broad overview of several metaphor-based algorithms, including the widely-used genetic and simulated annealing algorithms
Keywords :
genetic algorithms; simulated annealing; travelling salesman problems; combinatorial optimization problems; genetic algorithms; heuristic algorithms; metaphor-based algorithms; optimal solution; optimization algorithm; physical processes; simulated annealing algorithms; Cities and towns; Cost function; Evolution (biology); Genetic algorithms; Heuristic algorithms; Reliability engineering; Simulated annealing; Traveling salesman problems;
fLanguage :
English
Journal_Title :
Potentials, IEEE
Publisher :
ieee
ISSN :
0278-6648
Type :
jour
DOI :
10.1109/45.954644
Filename :
954644
Link To Document :
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