A Comparative Study of Cuckoo Algorithm and Ant Colony Algorithm in Optimal Path Problems

Finding the optimal path can be realized through a wide range of algorithms, which is demanded in many fields. Among countless algorithms that are used for solving the optimal path problem, the ant colony optimization (ACO) is one of the algorithms used to solve the approximate optimal path solution...

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Bibliographic Details
Published in:MATEC web of conferences Vol. 232; p. 3003
Main Author: Wang, Guanyu
Format: Journal Article Conference Proceeding
Language:English
Published: Les Ulis EDP Sciences 01.01.2018
Subjects:
Algorithms
Ant colony optimization
Comparative studies
Nesting
Search algorithms
Swarm intelligence
ISSN:2261-236X, 2274-7214, 2261-236X
Online Access:Get full text
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Summary:Finding the optimal path can be realized through a wide range of algorithms, which is demanded in many fields. Among countless algorithms that are used for solving the optimal path problem, the ant colony optimization (ACO) is one of the algorithms used to solve the approximate optimal path solution, while the cuckoo search (CS) algorithm is a swarm intelligence algorithm featuring Levy flight, whose core idea is derived from the cuckoo nesting property. In order to provide more ideas and directions for future research on optimal path problems, this paper discusses in detail the advantages and disadvantages of the two algorithms for solving the optimal path problem and their scopes of application by comparing principles and flows of the two algorithms.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/201823203003