A Study from the Perspective of Nature-Inspired Metaheuristic Optimization Algorithms

There are various metaheuristic algorithms which can be used to solve optimization problems efficiently. Among these algorithms, nature-inspired optimization algorithms are attractive because of their better results. In this paper, four types of metaheuristic algorithms such as ant colony optimizati...

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Bibliographic Details
Published in:International journal of computer applications 2015-01, Vol.113 (9), p.53-56
Main Authors: S, Deepthi, Ravikumar, Aswathy
Format: Article
Language:English
Subjects:
Algorithms
Ant colony optimization
Bats
Forages
Heuristic methods
Insects
Optimization
Swarming
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Summary:There are various metaheuristic algorithms which can be used to solve optimization problems efficiently. Among these algorithms, nature-inspired optimization algorithms are attractive because of their better results. In this paper, four types of metaheuristic algorithms such as ant colony optimization algorithm, firefly algorithm, bat algorithm and cuckoo search algorithms were used as the basis for comparison. Ant colony optimization algorithm is based on the interactions between social insect, ants. Firefly algorithm is influenced by the flashing behavior of swarming firefly. Cuckoo search uses brooding parasitism of cuckoo species and bat algorithm is inspired by the echolocation of foraging bats.
ISSN:0975-8887
0975-8887
DOI:10.5120/19858-1810