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Study of TSP based on self-organizing map
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作者 宋锦娟 白艳萍 胡红萍 《Journal of Measurement Science and Instrumentation》 CAS 2013年第4期353-360,共8页
Self-organizing map(SOM) proposed by Kohonen has obtained certain achievements in solving the traveling salesman problem(TSP).To improve Kohonen SOM,an effective initialization and parameter modification method is dis... Self-organizing map(SOM) proposed by Kohonen has obtained certain achievements in solving the traveling salesman problem(TSP).To improve Kohonen SOM,an effective initialization and parameter modification method is discussed to obtain a faster convergence rate and better solution.Therefore,a new improved self-organizing map(ISOM)algorithm is introduced and applied to four traveling salesman problem instances for experimental simulation,and then the result of ISOM is compared with those of four SOM algorithms:AVL,KL,KG and MSTSP.Using ISOM,the average error of four travelingsalesman problem instances is only 2.895 0%,which is greatly better than the other four algorithms:8.51%(AVL),6.147 5%(KL),6.555%(KG) and 3.420 9%(MSTSP).Finally,ISOM is applied to two practical problems:the Chinese 100 cities-TSP and102 counties-TSP in Shanxi Province,and the two optimal touring routes are provided to the tourists. 展开更多
关键词 self-organizing maps (SOM) traveling salesman problem (TSP) neural networkdocument code:AArticle ID:1674-8042(2013)04-0353-08
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