【作者】 杨亚璪；

【导师】 靳文舟；

【作者基本信息】 华南理工大学 ， 物流工程与管理， 2010， 博士

【摘要】 当前,收益管理的应用研究已经涉及到很多行业,在汽车租赁业中主要包括四个方面,即需求预测、预订、车队调度和定价策略,其中,车队调度是一项核心的研究内容。租赁车队调度是汽车租赁商对车辆物流的优化过程,可以具体分为战略车队调度和战术车队调度,在战略车队调度之前,还需要进行联营区的划分。租赁车队优化调度的研究目的是合理配置车队资源,降低车辆物流成本,提高企业的物流运作效率。由于汽车租赁站点的需求波动较大,顾客的租车行为随机性较强,车辆的种类较多,而且还存在车辆升级供应的情况,因此,车队调度问题是收益管理在汽车租赁业应用研究的难点之一。本文围绕租赁车队优化调度过程研究了几个关键问题,包括联营区划分、战略车队调度、战术车队调度和车辆路径问题,主要工作和研究成果如下:(1)根据租赁站点联营区划分的原则和三个限制性条件,提出一种基于P中值模型的联营区划分方法,并设计了启发式算法求解该问题,可以一次性获得联营区划分的结果和区域管理中心的位置。当租赁站点的需求或站点个数发生变化,需要调整部分联营区归属时,该模型可以获得满意解。(2)介绍了战略车队调度的主要任务,并以物流成本最小为目标建立了战略车队调度模型,保证了各联营区的车辆供给能够充分满足实际需求。在满足需求的同时,考虑了车辆调运过程中专用运输车的数量及其行驶路线,并借用集送货可拆分的车辆路径问题解决该难题,保证了物流成本最小。(3)介绍了车辆路径问题中常用的几种线路构造法和线路改进法,在已有算法的基础上,提出一种三阶段启发式算法求解集送货可拆分的车辆路径问题。首先根据任务点的集送货需求量确定所需车辆数目,然后采用足够多的车辆访问能够同时满载送货和满载集货的任务点,接着根据送货量、集货量和车辆剩余容量间的动态关系,采用剩余的车辆完成剩余的集送货任务,最后对已有线路进行改进,得到车辆的最终行驶线路。算例结果表明,该算法与已有算法相比可以明显降低运输成本。(4)由物流成本、车辆使用成本和企业收益的角度出发,基于租赁站点对各类车型的巢式需求特征,分别考虑需求固定和随机情况下问题的复杂性,给出单个联营区内多站点多车型条件下,采用升级供应策略实现车队资源优化配置的求解模型和求解思路,并设计算法进行求解。对于需求随机的情况,借助企业的车辆使用成本构建出一个产销平衡的运输问题,以求得各站点各车型的具体配置量。(5)将车辆调配情况抽象到时空网络结构中,并根据车辆需求的供应策略和时空节点的流量平衡得到约束条件,以企业运营成本最小为目标建立优化模型。针对模型特点采用奔德斯分解算法将原问题分解为两类子问题,给出对应的算法步骤。以一周为战术调度期设计算例,对模型和算法的有效性进行检验,结果表明能够为车队优化调配提供较好的辅助决策支持。更多还原

【Abstract】 Currently, the application of revenue management has been involved in many industries. The application in car rental industry include mainly four aspects, i.e., demand forecasting, booking, fleet planning and pricing, in which fleet planning is a core team of content. Rental fleet planning is the vehicle logistics optimization process by the car rental company, it can be divided into strategic fleet planning and tactical fleet planning, and before the strategic fleet planning, there needs to segment the pools. Optimizing planningof rental fleet is to optimize the allocation of fleet resources, and reduce the vehicle logistics costs as well as improve the efficiency of logistics operation. As the fluctuation of demand at car rental locations, the customers’random behavior, the distinct types of cars, and the upgrade supply policy, fleet planning in car rental industry is one of the most difficult problems in the application of revenue management.This paper focuses on several key issues in the process of optimizing rental fleet planning, including the pool segmentation, strategic fleet planning and tactical fleet planning. The main work and research results are as follows:According to the pool segmentation principle and three constraint conditions, this paper puts forward a pool segmentation method based on the P-median model, and designs a heuristic algorithm to solve the question, which can obtain the pool segmentation results and regional logistics center position. The model need to adjust the ownership of some sites and can get the satisfactory solution when the demand or the number of leasing sites change.The main tasks of the strategic fleet planning are described, and relevant mathematic model is proposed according to the aim of minimum logistics cost, which can guarantee the actual demand in each pool to be meet. The number and their routes of Car/auto shipping truck is optimized by the vehicle routing problem with split deliveries and pickups, which can meet the demand and make sure the minimum logistics costs.Several common construction methods and improving methods are described, and a three-phase heuristic algorithm to solve the vehicle routing problem with split deliveries and pickups is proposed based on the existing algorithms. First, according to the deliveries and pickups demands of task points, the number of vehicles can be confirmed. Second, visit task points which can delivery and pickup fully at the same time with the sufficient vehicles. And then, the remaining tasks of deliveries and pickups are accomplished by the remaining vehicles, in the light of the dynamic relations among deliveries, pickups and the remaining capacity of currently vehicle. At last, improve the existing routes and get the ultimate vehicle routes. The results of examples show that the algorithm can significantly reduce the transportation costs than the existing algorithms.From the angle of logistics costs, vehicle using costs and company revenue, and based on the nested demand characters of leasing sites, this study builds one-stage models to optimize resource allocation for multi-site and multi-type in a pool and puts forward solution methods for the circumstance of fixed demand and stochastic demand, respectively. By the aid of car use cost, a dummy balanced transportation problem is given for stochastic demand, which can obtain the detailed allocation amount at each site.Optimization model is set up with an objective of minimum operation cost. The fleet planning among rental locations is abstracted as a time-space network, and constraints are obtained according to the supply policy and flow balance at each node. Aimed at the characters of model, original problem is divided into two kinds of sub-problem by the use of Benders decomposition, and corresponding algorithm is proposed subsequently. A numerical example based on one week demonstrates the effectiveness of the proposed model and algorithm. The results indicate that the model and algorithm could be a promising way to improve the management quality of fleet planning.更多还原