需求可拆分车辆路径优化模型与BLF-GA算法设计

Researching on Optimization Model and BLF-GA Algorithm of Split Delivery Vehicle Routing Problem with two-dimensional loading Constraints

生活中,零售商或者顾客需求通常由具有一定尺寸的多件货物构成,这就使得车辆配送不仅应考虑车辆载货重量的限制,还应考虑车辆载货容积的限制.而多件货物构成的需求在很多情况下是允许多台车辆配送来满足,即需求可拆分.基于以上现实情况,笔者建立了考虑二维装箱约束的需求可拆分车辆路径优化模型,给出了模型解的特征.以改进的遗传算法为基础,结合BLF算法,设计了BLF-GA算法.数值案例表明:不考虑装箱约束得到的最优路线存在不满足装箱约束的情况,考虑装箱约束得到的最优值大于不考虑装箱约束的最优值,这说明货物尺寸对车辆路径产生了影响,在车辆路径优化中考虑装箱约束.

In life, the retailer or customers＂ demands are usually made up of multiple pieces of goods of a certain size, which makes the vehicle distribution not only take into account the weight of the vehicle load, but also the vehicle load volume restrictions. And demand consisted of multiple pieces of goods in many cases are to allow multiple vehicles to meet the distribution, that is, demand can be split. Based on the above reality, this paper establishes an optimization model of split delivery vehicle routing problem with two-dimensional loading constraints, and gives the characteristics of the model solution. Based on the improved genetic algorithm and BLF algorithm, BLF-GA algorithm is designed. The numerical examples show that the opti- mal route obtained by considering the loading constraint does not satisfy the loading constraint, and the opti- mal value obtained by loading constraint is larger than the optimal value without considering the loading con- straint, which shows that the size of the goods have an impact on the vehicles＇ routes and loading constraints have been considered in vehicle routing problem.