- 著者
-
Rong-Long WANG
Li-Qing ZHAO
Xiao-Fan ZHOU
- 出版者
- 一般社団法人 電子情報通信学会
- 雑誌
- IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (ISSN:09168508)
- 巻号頁・発行日
- vol.E95.A, no.3, pp.639-645, 2012-03-01 (Released:2012-03-01)
- 参考文献数
- 24
- 被引用文献数
-
1
3
Ant Colony Optimization (ACO) is one of the most recent techniques for solving combinatorial optimization problems, and has been unexpectedly successful. Therefore, many improvements have been proposed to improve the performance of the ACO algorithm. In this paper an ant colony optimization with memory is proposed, which is applied to the classical traveling salesman problem (TSP). In the proposed algorithm, each ant searches the solution not only according to the pheromone and heuristic information but also based on the memory which is from the solution of the last iteration. A large number of simulation runs are performed, and simulation results illustrate that the proposed algorithm performs better than the compared algorithms.