A hybrid ant colony algorithm for the grain distribution centers location

Authors:
Le Xiao;Qiuwen Zhang
Affiliations:
Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, China and College of Information Science and Engineering, Henan University of Technology, Zheng ...;China Airborne Missile Academy, Luoyang, China
Venue:
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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Abstract

Grain distribution center is the pivot of a grain logistics system. To define the location of grain logistics distribution center is the key of grain logistics system analysis. In this paper, according to the characteristics and requirements in the selection of the location, a mathematical model applied to the location selection was established on the basis of lowest transportation cost. A hybrid ant colony algorithm was then used to solve the model, the algorithm is based on the combination of genetic algorithm and ant colony clustering algorithm. First, it adopts genetic algorithm to give information pheromone to distribute. Second, it makes use of the ant colony clustering algorithm to give the precision of the solution. The algorithm can avoid premature convergence and prevent fast local optimal solution. The instance demonstrates that the hybrid algorithm can effectively get the grain logistics center optimal solution.