Study of logistics distribution route based on improved genetic algorithm and ant colony optimization algorithm
DOI: 10.23977/iotea.2016.11003 | Downloads: 77 | Views: 6202
Author(s)
Sun Yi 1, Su Yue 1
Affiliation(s)
1 Beijing University of Posts and Telecommunications, 100876, China
Corresponding Author
Sun YiABSTRACT
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.
KEYWORDS
route optimization problem; improved ant colony algorithm; improved genetic algorithm; pheromone; 2-OPT sub_routes optimizationCITE THIS PAPER
Yue, S. and Yi, S. (2016) Study of logistics distribution route based on improved genetic algorithm and ant colony optimization algorithm. Internet of Things (IoT) and Engineering Applications (2016) 1: 11-17.
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