A Novel Ant Colony Optimization Algorithm in Application of Pheromone Diffusion

摘要：

Ant Colony Optimization (ACO) Algorithm is a novel stochastic search technology, which simulates the social behavior of ant colony. This paper firstly analyzes the shortcomings of basic ACO, then presents an enhanced ACO algorithm which is more faithful to real ants behavior in application of pheromone diffusion. By setting up the pheromone diffusion model, the algorithm improves the collaboration among the nearby ants. The simulation results show that the proposed algorithm can not only get much more optimal solutions but also greatly enhance convergence speed.

关键词： ACO algorithm ant colony system pheromone diffusion

作者: Peng Zhu Ming-sheng Zhao Tian-chi He

作者单位: Department of Information Management, Nanjing University, 210093 Nanjing, China Nanjing Forest Police College, 210046 Nanjing, China Nanjing University of Financial and Economics, 210046 Nanjing, China

会议类型: 国际会议

会议名称: International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)

会议地点: 无锡

会议语种:英文

页码: 1-8

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）