Application of ant colony optimization to logistics vehicle dispatching system
LI Xiujuan1,YANG Yue2,JIANG Jinye1,JIANG Liming1
1. School of Electronics and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China; 2. International School, Beijing University of Posts and Telecommunications, Beijing 102209, China
Abstract：The thorough research on ant colony algorithm points out that the ant colony algorithm has superiority in solving large nonlinear optimization problem. Through careful analysis of the deficiencies that genetic algorithm and particle swarm algorithm solve the problem of vehicle dispatching system, based on the advantage of ant colony algorithm and the own characteristics of vehicle dispatching system, the basic ant colony algorithm was improved in the paper, and the algorithm framework was created. Based on the linear programming theory, the article established mathematical model and operation objectives and constraints for vehicle dispatching system, and got the optimal solution of vehicle dispatching system problem with the improved ant colony algorithm. According to the optimal solution and the dispatching criterion real-time scheduling was achieved. The article used Java language to write a simulation program for comparing the improved particle swarm optimization algorithm and ant colony algorithm. Through the comparison, it is found a result that the improved ant colony algorithm is correct and effective to solve the vehicle dispatching optimization problem.
2013, Vol. 33 
