文章基本信息

标题：ACO, Its Modification and Variants
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作者：Akash Tayal ; Prerna Khurana ; Priyanka Mittal 等
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2014
卷号：9
期号：6
页码：310-326
DOI：10.14445/22312803/IJCTT-V9P159
出版社：Seventh Sense Research Group
摘要：Ant colony optimization (ACO) is a P based metaheuristic algorithm which has been proven as a successful technique and applied to a number of combinatorial optimization problems and is also applied to the Traveling salesman problem (TSP). TSP is a wellknown NPcomplete combinatorial optimization (CO) problem and has an extensive application background. The presented paper proposes an improved version of Ant Colony Optimization (ACO) by modifying its parameters to yield an optimal result. Also this paper shows the experimental results and comparison between the original ACO and Modified ACO. Further this paper proposes two variants of ACO according to their specific application. Various city distributions have also been discussed and compared.
关键词：Ant Colony Optimization (ACO); Artificial Ants (AA); Combinatorial Optimization (CO); Particle Swarm Optimization (PSO); Travelling Salesman Problem (TSP)