Intelligent Learning Ant Colony Algorithm

Abstract:

Ant colony algorithm is effective algorithm for NP-hard problems, but it also tends to mature early as other evolutionary algorithms. One improvement method of ant colony algorithm is studied in this paper. Intelligent learning ant colony algorithm with the pheromone difference and positive-negative learning mechanism is brought forward to solve TSP. The basic approach of ant colony algorithm is introduced firstly, then we introduced the individual pheromone matrix and positive-negative learning mechanism into ant colony algorithm. Next the steps of intelligent learning ant colony algorithm are given. At last the effectiveness of this algorithm is proved by random numerical examples and typical numerical examples. It is also proved that intelligent ant and learning mechanism will affect concentration degree of pheromone.

• Periodical: Applied Mechanics and Materials (Volumes 48-49)
• Pages: 625-631
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.48-49.625
• Online since: February 2011
• Authors: Jian Hua Ma, Fa Zhong Tian
• Keywords: Ant Colony Algorithm (ACA), Intelligent Ant Colony, Learning Mechanism, TSP

References

[1] Colorni A, Dorigo M, Maniezzo V, in: Distributed Optimization by Ant Colonies[C]. Proc of 1st European conf Artificial Life, Pans, France: Elsevier, (1991).

[2] Colorni A, Dorigo M, Maniezzo V, in: An Investigation of Some Properties of an Ant Algorithm[C]. Proc. Of parallel Problem Solving from Nature (PPSN), France: Elsiver, (1992).

[3] Colorni A, Dorigo M, Maniezzo V, etc, in: Ant system for job2shop scheduling [J]. Belgian J of Operations Research Statistics and Computer Science, 1994, 34 (1): 39～53.

[4] WU Bin, SHI Zhong-Zhi, in: An Ant Colony Algorithm Based Partition Algorithm for TSP[J]. Chinese Journal of Computers, 2001, 24(12): 1328-1333.

[5] ZHAO Peixin, MA Jianhua and ZHAO Bingxin, in: A New Ant Colony Optimization Algorithm for Stochastic Loader Problem [J]. Systems Engineering-Theory & Practice, 2006, 26(8): 109-115.

[6] Jianhua Ma, Jie Yuan, Qi Zhang, in: Ant Colony Algorithms for Multiple-Depot Vehicle Routing, The proceedings of 2009 conference on systems science, management science & system dynamics, 2009(5): 55 -60.

[7] YIN Ren-kun, WU Yang and ZHANG Jing-wei, in: Research and Application of the Ant Colony Algorithm in the Assignment Problem [J]. Computer Engineering & Science, 2008(4): 43-45.

[8] HU Xiangpei, DING Qiulei and LI Yong-xian, in: A Review on Ant Colony System [J], Journal of Industrial Engineering and Engineering Management. 2008, 22(12): 74-79.

[9] Gambardella LM, Taillard E, Agazzi G. MACS2VRPTW, in: A Multiple Ant Colony System for Vehicle Routing Problem with Time Windows[J ]. New Ideas in Optimization, 1999: 63-76.

[10] LIU Zhishuo, SHEN Jinsheng and CHAI Yue-ting, in: Hybrid Multiple Ant Colonies Algorithm for Capacitated Vehicle Routing Problem [J]. Journal of System Simulation, 2007(15): 3513-3520.

DOI: 10.1109/icebe.2005.117

[11] Information on http: /www. iwr. uni-heidelberg. de/groups/comopt/software/TSPLIB95/tsp.

[12] Ma Jianhua, in: A Mutation Ant Colony Optimization Algorithm of Single Batch Machine Scheduling Problem [J]. Computer Engineering and Applications, 2006, 42(3): 53-56.