Improved Ant Colony Optimization for the Traveling Salesman Problem
The traveling salesman problem(TSP) in operations re search is a classical problem in discrete or combinato rial optimization. It is a prominent illustration of a class of problems in computational complexity theory which are classified as NP-hard. Ant colony optimization inspired by co-operative food retrieval have been widely applied unex pectedly successful in the combinatorial optimization. This paper presents an improved ant colony optimization algo rithm for traveling salesman problem, which adopts a new probability selection mechanism by using Held-Karp lower bound to determine the trade-off between the influence of the heuristic information and the pheromone trail The ex periments showed that it can stably generate better solution for the traveling salesman problem than rank-based ant sys tem and max-min ant colony optimization algorithm.
Lijie Li Shangyou Ju Ying Zhang
Ningbo City College of Vocational Technology No.9, Xuefu Road, Gaojiao District, Ningbo City, Zhejia Ningbo College of Health Sciences No.51, Xuefu Road, Gaojiao District,Ningbo City, Zhejiang Province
国际会议
长沙
英文
76-80
2008-10-20（万方平台首次上网日期，不代表论文的发表时间）