科技创新与应用2024，Vol.14Issue(29)：161-165,5.DOI:10.19981/j.CN23-1581/G3.2024.29.037
基于Transformer的旅行商问题解法
陆丽丹 1曹陆铖2
作者信息
- 1. 江苏联合职业技术学院,江苏 常熟 215500
- 2. 重庆大学 数学与统计学院,重庆 400044
- 折叠
摘要
Abstract
In approximate solutions to the traveling salesman problem(TSP),traditional heuristic algorithms are known for their slow convergence speed and low accuracy.To address these issues,this paper proposes a neural network approach based on Transformers.This method utilizes neural networks to effectively improve the speed and accuracy of approximate solutions,while leveraging the Transformer's attention mechanism to enhance the overall performance of the neural network.This method uses reinforcement learning for training and beam search algorithm for search.This method is used to test the random 50-node traveling salesman problem,and the experimental results show that the solution of the traveling salesman problem based on Transformer can get the effect which is similar to the exact solution under the premise of low complexity.关键词
旅行商问题/Transformer/注意力机制/神经网络/近似求解Key words
traveling salesman problem/Transformer/attention mechanism/neural network/approximate solution分类
信息技术与安全科学引用本文复制引用
陆丽丹,曹陆铖..基于Transformer的旅行商问题解法[J].科技创新与应用,2024,14(29):161-165,5.
