Abstract: The vehicle outbound intelligent scheduling is a difficult problem in the automotive logistics industry.Based on the practice of the industry,a three-layer decision model for the distribution of vehicle orders in the automotive logistics service supply chain was established to maximize customer satisfaction and minimize the total cost of logistics service,with the constraints such as transportation mode,loading tools and functional logistics service providers.The first layer was a selection model of transport mode with the goal of in-time delivery and low cost;the second layer was the vehicle stowage model aiming at maximizing the loading value;the third layer was a selection model of functional logistics service provider aiming at maximizing functional logistics service provider satisfaction.Based on the idea of hierarchical optimization and comprehensive integration,a hierarchical solution was proposed,and a heuristic algorithm was proposed for the large-scale solution of transport mode selection.The simulation experiments found that:the heuristic algorithm had good solution quality and efficiency when compared with Gurobi,NSGA-Ⅱ and Multi-objective Particle Swarm Optimization(MOPSO)algorithms for solving different scale cases;the influence of the objective preference of transport mode selection problem on the objective value showed a segmented linear relationship;the vehicle stowage model could optimize the stowing according to the order attributes on the basis of minimizing the number of loading tools to maximize the load capacity;the selection model of functional logistics service provider could improve global functional logistics service providers satisfaction effectively.Finally,numerical calculation based on practical data showed that the proposed model and algorithm were reasonable and effective.

Key words: vehicle outbound logistics, intelligent scheduling, logistics service supply chain, the three-layer decision model, heuristic algorithms

摘要： 整车出厂智能调度是汽车物流行业的痛难点。基于业内运作实践,以最大化客户满意度和最小化物流成本为总目标,考虑运输方式、承运车、物流服务提供商等约束,建立整车物流服务供应链中整车出厂物流订单分配的三层决策模型。第一层是以最小化延期交付时间和物流成本为目标的运输模式选择模型;第二层是以最大化装载价值为目标的车辆配载模型;第三层是以最大化物流服务提供商满意度为目标的物流服务供应商选择模型。随后,基于分层优化和综合集成思想,提出了分层求解思路,并针对运输方式选择大规模求解提出一种启发式算法。仿真实验发现:在不同规模算例下与Gurobi求解器、NSGA-Ⅱ、多目标粒子群优化(MOPSO)算法进行求解对比,启发式算法具有良好的求解质量和求解效率;运输方式选择问题目标偏好对目标值的影响呈分段线性关系;车辆配载模型在最小化承运车数量实现最大化装载量的基础上,可根据订单属性实现优化配载;物流服务供应商选择模型相较整车订单分配现状,可有效提升全局物流服务供应商满意度。最后,通过实践案例,进一步验证了模型算法的可行性与有效性。

关键词: 整车出厂物流, 智能调度, 物流服务供应链, 三层决策模型, 启发式算法