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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Veröffentlicht in:MATEC web of conferences Jg. 232; S. 3003
1. Verfasser: Wang, Guanyu
Format: Journal Article Tagungsbericht
Sprache:Englisch
Veröffentlicht: Les Ulis EDP Sciences 01.01.2018
Schlagworte:
Algorithms
Ant colony optimization
Comparative studies
Nesting
Search algorithms
Swarm intelligence
ISSN:2261-236X, 2274-7214, 2261-236X
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Zusammenfassung: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.
Bibliographie: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