Study of logistics distribution route based on improved genetic algorithm and ant colony optimization algorithm
DOI: 10.23977/iotea.2016.11003 | Downloads: 41 | Views: 3284
Sun Yi 1, Su Yue 1
1 Beijing University of Posts and Telecommunications, 100876, China
Corresponding AuthorSun Yi
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.
KEYWORDSroute optimization problem; improved ant colony algorithm; improved genetic algorithm; pheromone; 2-OPT sub_routes optimization
CITE 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.
 CHEN Hua-you. Theory and application of combination forecasting method [M]. Beijing: Science Press, 2008
 Bischoff C W. The combination of macroeconomic forecasts[J]. Journal of Forecasting, 1989, 8(3): 293-314
 LI Shi-yong, LI Pan-chi. A quantum ant colony algorithm for solving continuous space optimization problems [J].Control theory and application, 2008, 25 (2): 237-241
 CHEN Wei-dong, WANG Jia. Optimization of logistics distribution route based on hybrid ant colony algorithm [J]. computer engineering and design, 2009, 30 (14): 3383-3385
 WANG Hui, REN Chuan-xiang, YIN Chang-chang,Etc. Study on the optimization of logistics distribution route based on Niche Genetic Algorithm[J]. Application Research of computers, 2009.29(10): 2862-2865.
 JTJ 026-1-1999, Code for design of ventilation and lighting of highway tunnel[S]
 LANG Mao-xiang, HU Si-ji. Study on the optimization of physical distribution routing problem by using hybrid genetic algorithm[J]. Chinese Journal of Management Science, 2002, 10(10): 51-56.
 YANG Rui-chen, YUN Qin-xia. Improved ant colony algorithm in mine logistics distribution path[J]. 2004, 28(6): 16-18.