摘要
针对给定的设施点和客户点信息,建立了完整的LAP-VRP数学模型,LAP用于选址模型研究,VRP用于车辆路径优化分析。采用量子粒子群算法对LAP进行求解,将选址结果应用到VRP模型中,并通过蚁群算法对带时间窗和不带时间窗的VRP问题进行了求解。仿真结果表明,基于量子粒子群算法和蚁群算法的LAP-VRP模型求解具有较强的全局寻优能力,能够在较短时间内找到最优解,是解决物流配送路径优化的有效算法。
In this paper, we built a whole LAP-VRP mathematic model based on the given establishment points and customer points, while LAP was applied in the base station location and VRP was applied in the optimization analysis of vehicle routing. Then we used the quantum particle swarm algorithm to be the solution of the LAP model and applied its results into the VRP model. Hence the VRP model, with and without time win- dows could be solved by the ant colony algorithm. The experiment result showed that QPSO and ACO algorithm had a strong global search ability, which could efficiently solve the LAP-VRP problem in the shortest time, hence, the method presented was an effective algorithm to solve the routing problem.
出处
《物流技术》
2015年第16期131-135,共5页
Logistics Technology
关键词
量子粒子群算法
蚁群算法
物流配送
路径优化
quantum particle swarm algorithm
ant colony algorithm
logistics distribution
path optimization
