Research on Solving Traveling Salesman Problem Based on Virtual Instrument Technology and Genetic-Annealing Algorithms

被引：0

作者：

Chen, Muhao ^{[1
]}

Gong, Chen ^{[1
]}

Li, Xiaolong ^{[1
]}

Yu, Zongxin ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Wuhan, Peoples R China

来源：

2015 CHINESE AUTOMATION CONGRESS (CAC) | 2015年

关键词：

TSP; genetic algorithms; annealing algorithms; virtual instrument technology;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

TSP (Travelling Salesman Problem) is a typical issue of combinatorial optimization problem in the domain of mathematics, which aims at finding the shortest pathway among the given cities, and visit each city only once. This essay introduces an efficient way to solve TSP based on virtual instrument technology, combining the genetic algorithm and annealing algorithm. Because it takes the advantage of global and local optimization of the two algorithms. Finally, this paper proves that using the genetic algorithm result as the initial condition of the annealing algorithm method is a better way to obtain the best pathway. The visible result displays and testes the validity of this method.

引用

页码：1825 / 1827

页数：3

共 7 条

[1]

Araujo A. F. R., 2006, Proceedings. 20th International Conference on Advanced Information Networking and Applications

[2] A fast and elitist multiobjective genetic algorithm: NSGA-II [J].

Deb, K ;

Pratap, A ;

Agarwal, S ;

Meyarivan, T .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197

[3]

Fletcher R, 2000, PRACTICAL METHODS OP, P76

[4] Genetic algorithms for route discovery [J].

Gelenbe, Erol ;

Liu, Peixiang ;

Laine, Jeremy .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2006, 36 (06) :1247-1254

[5]

Kanoh Hitoshi, 2000, INT C KNOWL BAS INT, P616

[6]

Luger George F., 2010, ARTIFICIAL INTELLIGE

[7]

Selamat A, 2003, SICE 2003 ANNUAL CONFERENCE, VOLS 1-3, P2088

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