DocumentCode :
2344462
Title :
A New Design of Genetic Algorithm for Solving TSP
Author :
Yu, Yingying ; Chen, Yan ; Li, Taoying
Author_Institution :
Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China
fYear :
2011
fDate :
15-19 April 2011
Firstpage :
309
Lastpage :
313
Abstract :
In this paper, we develop an algorithm that is able to quickly obtain an optimal solution to TSP from a huge search space. This algorithm is based upon the use of Genetic Algorithm techniques. The algorithm employs a roulette wheel based selection mechanism, the use of a survival-of-the-fittest strategy, a heuristic crossover operator, and an inversion operator. To illustrate it more clearly, a program based on this algorithm has been implemented, which presents the changing process of the route iteration in a more intuitive way. Finally, we apply it into a TSP problem with fifty cities. By comparing with other published techniques, we can easily know that the proposed algorithm can efficiently complete the search process and derive a better solution.
Keywords :
genetic algorithms; search problems; travelling salesman problems; TSP optimal solution; TSP problem; genetic algorithm; heuristic crossover operator; inversion operator; roulette wheel based selection mechanism; route iteration; search process; search space; survival-of-the-fittest strategy; travelling salesman problem; Algorithm design and analysis; Biological cells; Cities and towns; Computers; Encoding; Genetic algorithms; Optimization; GA; TSP; crossover operator; mutation operator; selection operator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
Type :
conf
DOI :
10.1109/CSO.2011.46
Filename :
5957668
Link To Document :
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