Analysis of the Number of Ants in Ant Colony System Algorithm

被引：0
|
作者：
Alobaedy, Mustafa Muwafak [1 ]
Khalaf, Ali A. [2 ]
Muraina, Ishola D. [1 ]
机构：
[1] Univ Utara Malaysia, Changlun, Malaysia
[2] Univ Baghdad, Baghdad, Iraq
来源：
2017 5TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICOIC7) | 2017年
关键词：
Ant Colony System; Ant Colony Optimization; Parameters Analysis; Metaheuristic Algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This study presents an analysis of the number of ants in ant colony system algorithm. The study focuses on the effect of changing the number of ants in the algorithm behavior rather than find the optimum number. The factors investigated in this study are algorithm execution time, best solution, pheromones accumulative, pheromone dispersion, and the number of new solutions found by the ants. The experiment was conducted using travelling salesman problem to investigate those factors. The results show that the number of ants changes the algorithm behavior dramatically. Therefore, tuning the parameter number of ants in ant colony system could be easier by applying the min and max number of ants recommended in this study.
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页数：5
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