期刊名称：International Journal of Intelligent Systems and Applications
印刷版ISSN：2074-904X
电子版ISSN：2074-9058
出版年度：2021
卷号：13
期号：1
页码：45-59
DOI：10.5815/ijisa.2021.01.04
出版社：MECS Publisher
摘要：Genetic Algorithm often bears with Premature Convergence for solving combinatorial optimization problems but can be improved by modification at various step with different prospective. In this research, an effective knowledge is applied in the procedure of Genetic Algorithm used for solving TSP. The key concept for the purposed GA is modification in crossover operators by applying knowledge of smallest distant cities (shortest edge) assuming that it would improve the process to find the shortest path, hence can find the improved shortest path as well as decrease the problem of Premature Convergence. In the purposed method, crossover point selection for crossover operators depends upon the minimum edge presented in the given graph. To show the proposed method of knowledge application, Linear Order Crossover, Cycle Crossover Operator and Sequential Constructive Crossover are modified and results are proved on the random generated data sets for TSP.
