題名: | Hybrid Fuzzy C-means Clustering and Particle Swarm Optimization Algorithms for Traveling Salesman Problems |
作者: | 馮, 玄明 Jr 廖, 國隆 Jr |
關鍵字: | Traveling Salesman Problem Particle Swarm Optimization Simulated Annealing Fuzzy C-means Clustering |
期刊名/會議名稱: | NCS 2009 |
摘要: | It is true that the normal TSP can be proved as the well-known NP-Complete (Non-Deterministic Polynomial) path searching problems. The more cities’ nodes number will cause more complex traveling path problems. This paper combines the Particle Swarm Optimization (PSO), Transfer Space (TS) and Simulated Annealing (SA) to build the PSO-TS-SA algorithm. The Fuzzy C-means Clustering (FCM) algorithm is determined to reduce the complexity of large scale traveling cities. From the experiments on several TSP, the proposed hybrid fuzzy C-means clustering and particle swarm optimization Algorithms achieve more accuracy in the lower cost of computation time. |
日期: | 2011-02-21T23:27:55Z |
分類: | 2009年 NCS 全國計算機會議 |
文件中的檔案:
檔案 | 描述 | 大小 | 格式 | |
---|---|---|---|---|
AB 2-4.pdf | 339.69 kB | Adobe PDF | 檢視/開啟 |
在 DSpace 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。