期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：11
页码：169-180
出版社：SERSC
摘要：Ant colony algorithm (ACA) is a new heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. An Granular ACA algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature convergence problem of the basic ACA algorithm on TSP. Proposesing a Granular computing adaptive ant pheromones mechanism base on researching on ant colony algorithm model, pheromones update and pheromones selection had been improved. Make up the traditional ant colony algorithm for the calculation of distribution network planning that is slow and easy to fall into local optimal solution. And improved the convergence of the optimal solution. The validity of the GACA has been verified using a testing function. In addition, a satisfactory optimum solution for a Power Distribution Network Planning that has 73 users has been obtained.
关键词：Granular Ant Colony Algorithm; Power Distribution Net wo;ke Planning; ;Optimization; ;dynamic adaptive
