期刊論文
| 學年 | 104 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2015-10-01 |
| 作品名稱 | Imperial competitive algorithm with policy learning for the traveling salesman problem |
| 作品名稱（其他語言） | |
| 著者 | Chen, M. H.; S. H. Chen; P. C. Chang |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Soft Computing 21(7), pp 1863–1875 |
| 摘要 | The traveling salesman problem (TSP) is one of the most studied combinatorial optimization problems. In this paper, we present the new idea of combining the imperial competitive algorithm with a policy-learning function for solving the TSP problems. All offspring of each country are defined as representing feasible solutions for the TSP. All countries can grow increasingly strong by learning the effective policies of strong countries. Weak countries will generate increasingly excellent offspring by learning the policies of strong countries while retaining the characteristics of their own country. Imitating these policies will enable the weak countries to produce improved offspring; the solutions generated will, therefore, acquire a favorable scheme while maintaining diversity. Finally, experimental results for TSP instances from the TSP library have shown that our proposed algorithm can determine the salesman’s tour with more effective performance levels than other known methods. |
| 關鍵字 | Traveling salesman problem;Imperial competitive algorithm;Combinatorial optimization problems;Artificial chromosomes;Genetic algorithm |
| 語言 | en |
| ISSN | 1432-7643 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | DEU |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121451 ) |