Volume : VII, Issue : XII, December - 2018

An improved genetic algorithm for solving traveling salesman problem

Yan Wanjie, Wan Zhenkai

Abstract :

 It is very important to solve the traveling salesman problem accurately in many fields of scientific research, such as spaceflight, satellite and so on. By studying the traveling salesman optimization problem, several heuristic techniques are adopted to reduce the mutation rate and crossover rate with time, and the adaptive algorithm is used to calculate the average population fitness and the current optimal fitness of the population and to update its parameters. The algorithm is improved by carefully designing application program, introducing elite operator, eliminating operator and terminating checking method. Twenty data sets are extensively experimented and compared with four existing methods. The results show that the improved genetic algorithm can significantly improve the accuracy and convergence of genetic algorithm and effectively avoid the problem of local optimal solution. And can achieve two orders of magnitude acceleration effect 

Article: Download PDF    DOI : https://www.doi.org/10.36106/paripex  

Cite This Article:

An improved genetic algorithm for solving traveling salesman problem , Yan Wanjie, Wan Zhenkai , PARIPEX-INDIAN JOURNAL OF RESEARCH : Volume-7 | Issue-12 | December-2018

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