协作运营网络收益协调模型与求解方案研究

为提高协作运营网络的稳定性,从收益角度,研究协作运营网络中各协作单元的收益协调问题.首先界定协作单元、协作运营、协作运营网络和协作运营网络收益概念;基于"合作博弈",建立协作运营网络收益协调数学模型,实现协作运营网络收益最大化和协作单元收益均衡化;借助"Shapley值",对协作运营网络收益协调模型进行求解,提出基于"收益补偿"的协调策略.对如何有效协调协作组织收益,提高运营过程中各协作单元的主动性和积极性具有实践价值.     

成品油配送多车舱车辆指派及路径优化问题研究

针对成品油配送中多车型、多车舱的车辆优化调度难题,综合考虑多车型车辆指派、多车舱车辆装载及路径安排等决策,以派车成本与油耗成本之和的总成本最小为目标,建立了多车型多车舱的车辆优化调度模型。为降低模型求解的复杂性,本文提出一种基于C-W节约算法的“需求拆分→合并装载”的车辆装载策略,并综合利用Relocate和Exchange算子进行并行邻域搜索改进,获得优化的成品油配送方案。最后,通过算例验证了本文提出的模型与算法用于求解大规模成品油配送问题的有效性。并通过数据实验揭示了以下规律:1)多车舱车辆相对于单车舱车辆在运营成本上具有优越性;2)大型车辆适合远距离配送,小型车辆适合近距离配送;3)多车型车辆混合配送相对于单车型车辆配送在运营成本上具有优越性。这些规律可为成品油配送公司的车辆配置提供决策参考。     

面向电商终端物流配送的电动车配置与路径集成优化

在电子商务终端物流配送方面,存在能力与需求的矛盾。一方面,电动车存在货物容量约束和电池电量约束,配送能力有限;另一方面,一个物流配送点需要为众多的消费者进行门到门的配送,配送任务繁重。针对电子商务环境下终端物流配送规模大、电动车货物容量和行驶里程有限的问题,建立电商终端物流配送的电动车配置与路径规划集成优化模型,并提出一种基于临近城市列表的双策略蚁群算法,实现物流配送电动车辆配置与配送路径集成优化。该模型以电动车辆数最少和总路径最短为目标,以电动车货物容量和电池续航里程为约束,是带容量的车辆路径问题的进一步扩展,属于双容量约束路径规划问题。双策略蚁群算法在货物容量和续航里程的约束下,将蚁群搜索策略分为两类,即基于临近城市列表的局部搜索策略和全局搜索策略,在提高搜索效率的同时防止陷入局部优化。最后,通过阿里巴巴旗下菜鸟网络科技有限公司在上海的30组真实配送数据进行了测试,验证双策略蚁群算法显著优于一般蚁群算法。     

基于公平与效率的城市应急车辆配置研究

在城市中,消防、医疗、警务等应急车辆的配置是城市管理的一个重要方面.对该问题进行了研究,提出了对其评价的两个标准:公平与效率.作者根据这两个标准建立数学模型,该模型可用于这类车辆的管理.     

储备率、铸币收益与经济增长

本文考察了储备需求所增加的铸币收益在货币内生增长模型中的增长效应 .假设政府把铸币收益用在教育和公共生产性开支且对私人厂商有正的外部性 .用两部门内生增长模型分析因储备需求带来的增长效用 ,该经济有唯一的均衡增长路径 ,政府开支存在最优配置 ,且通过数据模拟存在最优储备率 .同样也得了与 [1 ]相类似的结论 :储备率与经济增长率的Laffer曲线关系 .     

带时间窗的三维装载物流配送优化方法研究

针对城市物流配送优化研究在客户服务时间窗和货物装载方式合理结合方面存在的不足,考虑物流配送车厢货物装载方式与客户访问序列相关的特征对车厢空间进行合理的区域划分。首先,构建了包含配送中心的固定成本、配送车辆的运输成本、维修成本、租赁成本和违反时间窗惩罚成本的物流运营成本最小化和配送车辆空间利用率最大化的双目标优化模型;然后,提出一种结合遗传算法(GA)全局搜索能力和禁忌搜索算法(TS)局部搜索能力的GA-TS混合算法求解模型;最后,结合重庆市某配送中心的三维装载物流配送实例数据进行了优化计算,实验结果给出了带时间窗的三维装载物流配送路径优化方案,并进行了不同车厢空间分区模式下平均装载率、物流运营成本和车辆使用数的比较分析。研究表明,当客户需求货物种类数与车辆的空间区域划分数相等且按货物类型进行区域划分时,物流运营成本最小,配送车辆使用数最少和车辆平均装载率最高。     

基于Logit离散选择模型的品类优化问题综述

品类优化问题(Assortment Optimization Problem)是收益管理的经典问题.它研究零售商在满足运营约束的前提下,应如何从给定产品集合中选择一个子集提供给消费者,以最大化预期收益.该问题的核心在于如何准确地刻画消费者在面对细分产品时的选择行为、建立相应的优化模型并设计高效率的求解算法.基于Logit离散选择模型的品类优化问题:首先,介绍了基于Multinomial Logit模型的品类优化问题.然后介绍了两个更复杂的变种:第一个是基于两层以及多层Nested Logit模型的品类优化问题,这类问题可合理刻画细分产品之间的"替代效应";第二个是基于Mixtures of Multinomial Logits模型的品类优化问题,这类问题可充分考虑消费者群体的异质性.随后,介绍了数据驱动的品类优化问题的相关进展.最后,指出该问题未来可能的若干研究方向.     

基于可信性理论的PPP项目特许期-价格联合调整策略研究

需求预测误差是影响PPP项目收益预测准确性的主要因素。为减少谈判争议,确保风险和收益的动态均衡,本文基于模糊数学可信性理论,构建了考虑需求不确定的特许期-价格联合调整模型。将项目运营期间的需求预测误差作为模糊变量,将运营期内特许期和价格的联合调整策略作为决策变量,通过模糊模拟求解出不同特许期和价格调整组合下的期望收益误差以及正收益预期下的可信性,进而得到特许期和价格的联合调整策略可行解集。并将该模型应用于某污水项目中,结果表明,该模型能够有效地解决需求不确定性风险对特许期测算影响的问题,弥补了目前PPP项目特许期和价格调整决策研究中未考虑需求预测误差的不足,对PPP项目特许期和价格的调整决策有着重要的参考意义。     

投资者情绪对上证50ETF隐含分布偏度影响的实证研究

从期权价格中提取信息的传统做法是借助于隐含波动率,然而,通过与标的资产的历史数据对比发现,隐含波动率并不能比历史波动率提供更多的市场预期信息。考虑隐含波动率是利用Black-Scholes模型所导出,意味着模型设定风险也可能会影响到结论的客观性与准确性。为了克服传统方法的不足,本文尝试从一种无模型的视角,利用矩方法展开相关研究。该方法不依赖于任何模型和假设,避免了对定价核以及中性概率分布的讨论,直接由期权价格得到股票收益的隐含分布,利用状态价格来确定市场预期收益与风险厌恶。在分布曲线足够光滑(可导)的条件下,通过对行权价格求导得到标的资产未来收益的隐含风险中性概率密度,并测算出隐含分布的高阶矩特征。     

快件揽收实时车辆路径问题的一种贪婪算法

快递运营中，调派车辆前往随机发生的快件发件人处上门揽收快件，是一个实时编排行车路径的动态决策过程．本文针对该问题，采用了揽收所有快件的最后时刻最早和行车路径最短的目标，结合车辆揽收快件数平衡的要求，给出一种贪婪算法；然后，对Solomon设计的100个点规模的VRPTW算例做计算试验，分析了车辆数对目标的影响．     

互联网租车市场的演化博弈分析

通过分析互联网租车市场的出现对传统租车市场造成的影响,以探究通过何种策略避免两个租车市场的恶性竞争,构建了基于Bertrand模型的互联网租车方和传统租车方在合作与非合作条件下的静态博弈,结果显示两者在合作模式下会受困于个体理性与集体理性冲突的矛盾中。因此,为了解决这个矛盾,加入政府部门构建多主体合作演化博弈模型,推导出政府和两个租车市场的演化稳定策略,并对模型的演化路径和演化结果进行研究,以期为政府部门对租车市场的管理决策提供参考。     

A relax-and-fix-based algorithm for the vehicle-reservation assignment problem in a car rental company

Empty repositions are a major problem for car rental companies that deal with special types of vehicles whose number of units is small. In order to meet reservation requirements concerning time and location, companies are forced to transfer cars between rental stations, bearing significant costs and increasing the environmental impact of their activity due to the fuel consumption and CO₂${\text{CO}}_2$ emission. In this paper, this problem is tackled under a vehicle-reservation assignment framework as a network-flow model in which the profit is maximized. The reservations are allocated considering the initial and future availability of each car, interdependencies between rental groups, and different reservation priorities. To solve this model, a relax-and-fix heuristic procedure is proposed, including a constraint based on local branching that enables and controls modifications between iterations. Using real instances, the value of this approach is established and an improvement of 33% was achieved when compared to the company’s current practices.     

Revenue Models and Policies for the Car Rental Industry

In this paper, we consider the application of revenue management techniques in the context of the car rental industry. In particular, the paper presents a dynamic programming formulation for the problem of assigning cars of several categories to different segments of customers, with rental requests arising dynamically and randomly with time. Customers make a rental request for a given type of car, for a given number of days at a given pickup time. The rental firm can satisfy the demand for a given product with either the product requested or with a car of at most one category superior to that initially required, in this case an “upgrade” can take place. The one-way rental scenario, which allows the possibility of the rental starting and ending at different locations, is also addressed. In the framework considered, the logistic operator has to decide whether to accept or reject a rental request. Since the proposed dynamic programming formulations are impractical due to the curse of dimensionality, linear programming approximations are used to derive revenue management decision policies for the operator. Indeed, primal and dual acceptance policies are developed (i.e. booking limits, bid prices) and their effectiveness is assessed on the basis of an extensive computational phase.     

考虑顾客使用行为的汽车租赁容量分配策略研究

随着物联网技术的发展, 租赁公司通过智能技术可以实时监测顾客的使用行为, 因此可以根据顾客使用行为设计补贴策略以激励顾客在使用过程中保持良好的行为习惯。本文将租赁价格作为顾客行为的函数, 构建随机动态规划模型, 研究了多产品、多周期下汽车租赁公司的容量分配决策和补贴机制。考虑到所构建模型的状态变量维度较高, 因此提出两种近似算法对模型进行求解, 并通过数值仿真验证了模型的相关性质。在考虑顾客行为可以转变的前提下, 得到相关结论:租赁公司以机会成本作为容量分配决策的重要依据;当所需等级汽车缺货时, 由于低等级汽车的机会成本低于高等级汽车的机会成本, 因此满足升级条件时, 租赁公司总是按照等级顺序进行升级;在合理的补贴策略下, 公司的总收益将会随着补贴的增加而增加。     

Integrated revenue management approaches for capacity control with planned upgrades

In many service industries, firms offer a portfolio of similar products based on different types of resources. Mismatches between demand and capacity can therefore often be managed by using product upgrades. Clearly, it is desirable to consider this possibility in the revenue management systems that are used to decide on the acceptance of requests. To incorporate upgrades, we build upon different dynamic programming formulations from the literature and gain several new structural insights that facilitate the control process under certain conditions. We then propose two dynamic programming decomposition approaches that extend the traditional decomposition for capacity control by simultaneously considering upgrades as well as capacity control decisions. While the first approach is specifically suited for the multi-day capacity control problem faced, for example, by hotels and car rental companies, the second one is more general and can be applied in arbitrary network revenue management settings that allow upgrading. Both approaches are formally derived and analytically related to each other. It is shown that they give tighter upper bounds on the optimal solution of the original dynamic program than the well-known deterministic linear program. Using data from a major car rental company, we perform computational experiments that show that the proposed approaches are tractable for real-world problem sizes and outperform those disaggregated, successive planning approaches that are used in revenue management practice today.     

Fleet-sizing and service availability for a vehicle rental system via closed queueing networks

In this paper, we address the problem of determining the optimal fleet size for a vehicle rental company and derive analytical results for its relationship to vehicle availability at each rental station in the company’s network of locations. This work is motivated by the recent surge in interest for bicycle and electric car sharing systems, one example being the French program Vélib (2010). We first formulate a closed queueing network model of the system, obtained by viewing the system from the vehicle’s perspective. Using this framework, we are able to derive the asymptotic behavior of vehicle availability at an arbitrary rental station with respect to fleet size. These results allow us to analyze imbalances in the system and propose some basic principles for the design of system balancing methods. We then develop a profit-maximizing optimization problem for determining optimal fleet size. The large-scale nature of real-world systems results in computational difficulties in obtaining this exact solution, and so we provide an approximate formulation that is easier to solve and which becomes exact as the fleet size becomes large. To illustrate our findings and validate our solution methods, we provide numerical results on some sample networks.     

产能分享对设备制造商和用户企业的影响研究

本文建立Stackelberg博弈模型比较了传统制造模式与产能分享模式下设备制造商和设备用户企业的利润,发现设备用户企业总是从产能分享模式中受益,但是订单需求增量不同的企业受益大小不同;平台制定的设备租赁价格对设备制造商的利润和设备用户企业的购买决策都将产生影响,对于任意固定价格的设备,平台的制定的最优租赁价格是唯一的,并且平台的最优利润是设备价格的倒U型函数;产能分享业务的出现对设备制造商产生了损益影响,当平台采取最优的定价策略时,价格相对比较高的设备的购买需求增加,设备制造商从产能分享业务中受益,价格相对比较低的设备的购买需求降低,设备制造商在产能分享业务中利益受损。最后通过算例分析对上述结果进行了验证。     

Neighborhood effects and maintenance of the urban housing stock*

This paper presents and analyzes a theoretical model of the impact of neighborhood effects upon the maintenance of urban housing stock. The rental value of a dwelling unit is related not only to its own physical characteristics but also to those of other dwelling units in its neighborhood. The physical characteristics of dwelling units depend upon how much their owners spend on maintenance. Since these expenditures are undertaken only in so far as they enhance the rental value of properties, the maintenance policies of a neighborhood's owners are interdependent. The model focuses explicitly on the aspects of this process that involve multiperson decisions. Concepts concerning equilibrium are introduced; short run equilibria are shown to exist, and conditions for their uniqueness are derived. Comparative static results are established, and stability properties of the static equilibria analyzed.     

基于优惠合同的在线租赁策略设计

近年来租赁行业竞争日益激烈,租赁企业为了吸引客户有时会开展一些优惠活动。针对这一现状,本文讨论了存在优惠合同时承租方的在线租赁决策问题,其中假设该优惠合同 给予承租方一次以比较优惠的价格连续租赁设备多期的机会。首先,分析了存在优惠合同时的最优离线策略。其次,利用在线算法和竞争比理论分别设计了承租方放弃优惠合同和签订优惠 合同两种情形下的最优在线策略及最优竞争比。最后,通过汽车租赁优惠的数值算例说明选择签订优惠合同是更好的策略,进一步给出了签订优惠合同和购买设备的最佳时间。     

在线多租赁选择问题的最优竞争策略

在线算法与竞争分析是研究信息不确定决策问题的一种新工具,应用该方法研究在线租赁问题是近年来国内外的一个研究热点。传统的在线租赁问题以经典的"雪橇租赁模型"为基础,考虑在线决策者可以选择购买或按单位时间租赁的方式来使用设备。然而现实租赁市场(比如汽车租赁,房屋租赁)往往提供多种租赁方式供在线决策者选择,除了按单位时间进行租赁,通常可以以一个较优惠的价格租赁多个单位时间。在这种现实背景下,本文建立了多种租赁形式下的在线租赁模型,给出了这种租赁模型下的确定性竞争策略,并证明该策略具有最优竞争比。