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
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