文章基本信息

标题：Approaches to the Travelling Salesman Problem Using Genetic Algorithm Approaches
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作者：Ankur Sharma ; Ratan Mishra ; Vijay Maheshwari 等
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2013
卷号：4
期号：2
页码：178-180
语种：English
出版社：Ayushmaan Technologies
摘要：Travelling Salesman Problem (TSP) is an example of NP hard combinatorial optimization problem. In TSP salesman travels N citiesandreturns to the starting city with minimal cost, he is not allowed to cross the city more than once. To solve this problem we use Genetic Algorithm Approach as genetic algorithms are designed to solve NP hard problems. In this paper The Genetic Algorithm is used for initialization of population and improvement of offspring produced by crossover for a Traveling Salesman Problem (TSP). various solutions are considered during the search procedure, and the population evolves until a solution satisfies the termination criteria. The advantages of the GA over other heuristic methods for solving combinatorial optimization problems include massive parallelism and its ability to solve “non-linear” optimization problems where the search space is extremely large.
关键词：Genetic Algorithm (GA);Travelling Sales Man Problem (TSP); Crossover and Selection;on Roulette Wheel Process