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  • 标题:A Comparative Study of Cuckoo Algorithm and Ant Colony Algorithm in Optimal Path Problems
  • 本地全文:下载
  • 作者:Guanyu Wang
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:232
  • DOI:10.1051/matecconf/201823203003
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要: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.
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