Algorithm for Solving Traveling Salesman Problem Based on Self-Organizing Mapping Network

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外文摘要：Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter selection.This paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic algorithms.Simulations show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm accuracy.Compared with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.

外文关键词：

traveling salesman problem(TSP)self-organizing mapping(SOM)combinatorial optimizationneu-ral network

作者：

朱江辉、叶航航、姚莉秀、蔡云泽

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作者单位：

Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China

Key Laboratory of System Control and Information Processing,Ministry of Education,Shanghai 200240,China

Shanghai Engineering Research Center of Intelligent Control and Management,Shanghai 200240,China

Key Laboratory of Marine Intelligent Equipment and System,Ministry of Education,Shanghai 200240,China

Huawei Technologies Co.,Ltd.,Shanghai 201206,China

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基金：

National Natural Science Foundation of ChinaNational science and Technology Major Program of ChinaNational Defense science and Technology Outstanding Youth Science Foundation

项目编号：

616278102018YFB13050032017-JCJQ-ZQ-031

出版年：

2024

DOI：

10.1007/s12204-022-2517-3

上海交通大学学报(英文版)

上海交通大学

上海交通大学学报(英文版)

影响因子：0.151

ISSN：1007-1172

年,卷(期)：2024.29(3)