期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2013
卷号：3
期号：2
页码：264-267
出版社：International Journal of Soft Computing & Engineering
摘要：The Purpose of this Paper is to give near optimal solution in terms of quality and computation time. By implementing Genetic Optimization Technique, the effectiveness of the path has been evaluated in terms of fitness function with the parameter such as tour length. In this research work, we see different variation in traveling salesmen problem using Genetic Algorithm Technique. Considering the Limitation of Nearest Neighbor we find that the number of iteration and resulting time complexity can be minimized by using Genetic approach. We also compare the operator of pursued approach which give the best result for finding the shortest path in a shortest time for moving toward the goal. Thus the optimal distance with the tour length is obtained in a more effective way.
关键词：TSP; Fitness Function; Genetic Algorithm; Nearest;Neighbour; GA operators.
