Study of logistics distribution route based on improved genetic algorithm and ant colony optimization algorithm
Journal: Internet of Things (IoT) and Engineering Applications (Vol.1, No. 1)Publication Date: 2016-12-31
Authors : Sun Yi; Su Yue;
Page : 11-17
Keywords : route optimization problem; improved ant colony algorithm; improved genetic algorithm; pheromone; 2-OPT sub_routes optimization;
Abstract
To solve the problem of vehicle routing problem under capacity limitation, this paper puts forward a novel method of logistics distribution route optimization based on genetic algorithm and ant colony optimization algorithm (GA-ACO). On the first stage, improved genetic algorithm with a good global optimization searching ability is used to find the feasible routes quickly. On the second stage, the result of the genetic algorithm is used as the initial solution of the ant colony algorithm to initialize the pheromone. And then improved ant colony optimization algorithm is used to find the optimal solution of logistics distribution route. Experimental results show that the optimal or nearly optimal solutions of the logistic distribution routing can be quickly obtained by this two stages method.
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