Abstract:The structure and principle of ant colony algorithm are introduced. Its excellence and deficiency are analyzed, and several important improved models are reviewed. Based on MaxMin Ant Systems (MMAS), an adaptive improved model is put forward. To achieve adaptive adjustment of parameters and enhance the performance of the proposed algorithm, the weighting coefficient, state transferring rule and pheromone increment mode are improved. To testify the performance of the improved algorithm, numerical experiment is made and the result shows the improved algorithm is effective.
[1] Dorigo M, Maniezzo V, Colorni A. Positive Feedback as a Search Strategy. Technical Report, 91016, Politecnico di Milano, Italy: University of Padova. Department of Information Engineering,1991 [2] Dorigo M, Gambardella L M. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Trans on Evolutionary Computation, 1997, 1(1): 5366 [3] Stutzle T, Hoos H H. MaxMin Ant System. Journal of Future Generation Computer Systems, 2000, 16 (9): 889914 [4] Zhang Jihui, Xu Xinhe. A New Evolutionary Algorithm-Ant Colony Algorithm. Systems Engineering-Theory & Practice, 1999, 19(3): 8487 (in Chinese) (张纪会,徐心和.一种新的进化算法-蚁群算法.系统工程理论与实践, 1999, 19(3): 8487) [5] Wang Ying, Xie Jianying. An Adaptive Ant Colony Optimization Algorithm and Simulation. Journal of System Simulation, 2002, 14(1): 3133 (in Chinese) (王 颖,谢剑英.一种自适应蚁群算法及其仿真研究.系统仿真学报, 2002, 14(1): 3133) [6] Watanabe I, Matsui S. Improving the Performance of ACO Algorithms by Adaptive Control of Candidate Set // Proc of the Congress on Evolutionary Computation. Newport Beach, USA, 2003, Ⅱ: 13551362 [7] Lu Yong, Zhao Guangzhou, Su Fanjun. Adaptive AntBased Dynamic Routing Algorithm // Proc of the 5th World Congress on Intelligent Control and Automation. Hangzhou, China, 2004, Ⅲ: 26942697 [8] Ngo S H, Jiang Xiaohong, Horiguchi S. Adaptive Routing and Wavelength Assignment Using AntBased Algorithm // Proc of the IEEE International Conference on Networks. Singapore, Singapore, 2004: 482486 [9] Qin Gangli, Yang Jiaben. An Improved Ant Colony Algorithm Based on Adaptively Adjusting Pheromone. Information and Control, 2002, 31(3): 198201,210 (in Chinese) (覃刚力,杨家本.自适应调整信息素的蚁群算法.信息与控制, 2002, 31(3): 198201,210) [10] Li Yong,Duan Zhengcheng.A New Ant System for TSPs. Computer Engineering and Applications, 2003, 39(17): 103106 (in Chinese) (李 勇,段正澄.动态蚁群算法求解TSP问题.计算机工程与应用, 2003, 39(17): 103106) [11] Gao Jian. Cluster Analysis Based on Parallel Ant Colony Adaptive Algorithm. Computer Engineering and Applications, 2003, 39(25): 7879,82 (in Chinese) (高 坚.基于并行多种群自适应蚁群算法的聚类分析.计算机工程与应用, 2003, 39(25): 7879,82)