Hybrid Algorithm for Solving Traveling Salesman Problem

被引：2
作者：
Zhao, Ping [1 ]
Xu, Degang [1 ]
机构：
[1] Henan Univ Technol, Sch Informat Sci & Engn, Zhengzhou, Peoples R China
来源：
2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2019) | 2019年 / 646卷
关键词：
D O I：
10.1088/1757-899X/646/1/012032
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The basic genetic algorithm has the disadvantages of falling into local optimum and slow convergence. To solve this problem, a hybrid algorithm combining simulated annealing strategy is proposed. The cooling process in simulated annealing is used to complete the iterative process in the hybrid algorithm. The algorithm is used to solve the traveling salesman problem. The results show that the convergence speed and accuracy of the hybrid algorithm is significantly better than the basic genetic algorithm.
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页数：6
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