基于Multi-Logit模型的多机场系统航线补贴研究

随着我国民航业快速发展,机场密度不断提高,在一定地域范围内存在多个机场的现象.然而多机场系统内机场间竞争激烈,其中航线补贴已经成为国内大部分机场激励航空公司增加运力、开拓更多航线的重要手段.对于机场来说,如何科学的补贴很值得研究.从乘客出行选择角度着眼,利用Multinomial Logit模型考察了航线补贴对机场及航空公司的市场份额、机场自身利润及社会总收益的影响,从而给出补贴建议.研究表明:1)多机场系统内,一家航空公司的航线补贴增加时,这家航空公司及所在机场的市场份额增加,其余机场及航空公司市场份额均有所下降.2)多机场系统内大型机场补贴新航班航线时,对市场占有率高的航空公司补贴增加,航空公司市场份额、机场在这条航线上总利润以及社会总收益都随之增加.3)多机场系统内两家邻近中小机场,根据两家机场单位航线补贴方案不同,航空公司市场份额、机场在这条航线上总利润以及社会总收益也相应不同.     

基于动态服务网络的铁路紧急输送计划编制模型和算法

根据特殊条件下铁路输送计划问题的动态性、多目标性、时效性等特点,采用时空网络构建铁路输送计划网络模型.并建立了基于动态路径的铁路输送计划编制数学模型.模型属于大规模的整数规划,以追求时间效益最大化和灾害损失最小化为目标.根据模型的特点,提出了松弛求解算法,借助LINGO求解工具求解松弛模型,通过逐步固定变量为整数值求得最优解.算例研究表明,算法可行有效.     

基于动态服务网络的铁路紧急输送计划编制模型和算法北大核心

根据特殊条件下铁路输送计划问题的动态性、多目标性、时效性等特点,采用时空网络构建铁路输送计划网络模型.并建立了基于动态路径的铁路输送计划编制数学模型.模型属于大规模的整数规划,以追求时间效益最大化和灾害损失最小化为目标.根据模型的特点,提出了松弛求解算法,借助LINGO求解工具求解松弛模型,通过逐步固定变量为整数值求得最优解.算例研究表明,算法可行有效.     

竞争环境下基于乘客分类的航空客运机票控制和动态定价综合模型

假定航空公司以提供折扣票的方式将乘客分为两类,并通过动态控制折扣票的销售和对普通票实行动态定价来最大化自身的期望收益.应用动态规划建立了竞争环境下两航空公司的折扣机票控制和普通机票动态定价综合模型,讨论了普通机票价格均衡的存在性,并给出航空公司基于已卖出的机票数量接受或拒绝乘客购买折扣票的阈值.最后,通过算例讨论了不同参数对均衡价格、阈值和期望收益的影响.     

机队运力配置和USApHMP问题的联合决策模型与算法

针对USApHMP (无容量限制的单分配枢纽网络设计)方法忽略了航空公司航线运力配置决策对单位客流量成本的影响问题,以枢纽机场选址、确定枢纽与非枢纽连接关系、航线机型及其频次选择为决策变量,综合考虑各城市对市场需求量、航线最大飞行频次、机队可用飞行时间等限制因素,以实现航线运力配置成本和枢纽设置成本最小化为目标函数,建立航线机型匹配及频次选择问题和USApHMP问题的联合决策优化模型,设计遗传算法进行求解.算例分析表明:考虑4种机型、10个城市和90个城市对的情况,与传统枢纽网络设计方法相比,联合决策模型的网络总成本降低了9.39%,且航线最大飞行频次是影响枢纽网络设计方案的重要因素.     

基于乘客惰性行为的平行航班动态定价

在同一条航线上,航空公司提供起飞时间不同的多个航班,这样的航班称为平行航班。本文以同一航线上的多个平行航班为研究对象,在考虑乘客的惰性深度和惰性广度的基础上,利用动态规划方法,研究了乘客的惰性行为对各航班最优价格的影响。数值实验表明:乘客的惰性对各航班的最优价格起负面影响,即各航班的最优价格随乘客惰性深度的增加而减小,随乘客惰性广度的增加而减小。     

基于q-理论的家族企业动态模型

本文在不完全市场下,基于托宾q-理论,以最大化企业家的CRRA期望效用为目标,在假设企业资本和生产力均随机的条件下,研究家族企业的动态优化问题,即家族企业在动态经营过程中的生产、消费和投资组合的最优决策问题.利用动态规划原理推导出企业最优决策所满足的HJB方程,并通过企业适用的生产消费均衡理论和风险对冲需求对此HJB方程进行求解,得到家族企业的最优生产、最优消费和最优投资策略.最后选取合适参数对家族企业的最优策略进行数值分析,结果表明了企业的最优策略与其流动性之间的变化关系.     

随机利率环境下基于二次效用函数的动态投资组合(英文)

研究随机利率环境下基于效用最大化的动态投资组合,并假设利率是服从Ho-Lee利率模型和Vasicek利率模型的随机过程.应用动态规划原理得到值函数满足的HJB方程,并应用Legendre变换得到其对偶方程.最后,应用变量替换对二次效用函数下的最优投资策略进行研究,得到了最优投资策略的显示解.     

基于需求分类和乘客升级购买行为的航空公司收益管理模型

研究了基于乘客分类的航空客运库存控制与动态定价策略.模型中,航空公司以提供折扣票的方式将乘客分为两类,并针对购买折扣票的乘客存在升级购买行为,通过动态的控制折扣票的销售和对机票实施动态定价来最大化自身的期望收益.应用动态规划建立了相应的收益管理模型,讨论了最优定价应满足的关系式,并得到了接受或拒绝乘客购买折扣票的阈值.最后,通过算例分析了升级购买概率对阈值、机票的价格及期望收益的影响.     

基于动态VaR约束与随机波动率模型的最优投资策略

研究Stein-Stein随机波动率模型下带动态VaR约束的最优投资组合选择问题. 假设投资者的目标是最大化终端财富的期望幂效用,可投资于无风险资产和一种风险资产, 风险资产的价格过程由Stein-Stein随机波动率模型刻画. 同时, 投资者期望能在投资过程中利用动态VaR约束控制所面对的风险.运用Bellman动态规划方法和Lagrange乘子法, 得到了该约束问题最优策略的解析式及特殊情形下最优值函数的解析式; 并通过理论分析和数值算例, 阐述了动态VaR约束与随机波动率对最优投资策略的影响.     

The competitive salesman problem on a network: a worst-case approach

We provide a complexity analysis of the problem of optimal routing of a server on a transportation network in the presence of a competing server. The server that reaches a node first gets the profit from the node. The objective is to maximize the worst-case profit.     

需求不确定的多周期的容量决策问题

研究每个周期的需求随机增加的情形下的容量扩充问题,建立起切合实际的有限周期随机动态规划模型及在期现值准则下的无限周期随机动态规划模型,进而探索生产单一产品的公司在面对随机增加的市场需求时,风险中立的管理者该如何扩充其生产容量,才能使得其公司在折扣意义下的总期望利润最大.研究无限阶段的容量扩充问题,得出某种约束条件下的优化策略解,给公司管理者提供了其长期可持续发展的优化策略和依据.     

Models for planning capacity expansion of convenience stores under uncertain demand and the value of information

Several stochastic optimization models for planning capacity expansion for convenience store chains (or other similar businesses) are developed that incorporate uncertainty in future demand. All of these models generate schedules for capacity expansion, specifying the size, location, and timing of these expansions in order to maximize the expected profit to the company and to remain within a budget constraint on available resources. The models differ in how uncertainty is incorporated, specifically they differ in the point in the decision-making process that the uncertainty in the demand is resolved. Several measures of the value of information are defined by comparing the results from the different models. Two sample problems are given and their solutions for the various approaches compared.     

A stochastic approach to professional services firms’ revenue optimization

Regarding professional service time as perishable goods, it should be possible to directly migrate the successful airline revenue management techniques to professional services firms (PSFs) for their analogous business characters. However, there are salient differences between airlines and PSFs should be highlighted—the network structure of length-of-continuance and capacity allocation of multifunctional staff. Customers booking to be served from a first continuance time to a last continuance time in consecutive time continuance. Multifunctional professionals should be properly allocated to maximize the benefit. The arrival demands and lengths of service are stochastic in nature.     

Network capacity management under competition

We consider capacity management games between airlines who transport passengers over a joint airline network. Passengers are likely to purchase alternative tickets of the same class from competing airlines if they do not get tickets from their preferred airlines. We propose a Nash and a generalized Nash game model to address the competitive network revenue management problem. These two models are based on well-known deterministic linear programming and probabilistic nonlinear programming approximations for the non-competitive network capacity management problem. We prove the existence of a Nash equilibrium for both games and investigate the uniqueness of a Nash equilibrium for the Nash game. We provide some further uniqueness and comparative statics analysis when the network is reduced to a single-leg flight structure with two products. The comparative statics analysis reveals some useful insights on how Nash equilibrium booking limits change monotonically in the prices of products. Our numerical results indicate that airlines can generate higher and more stable revenues from a booking scheme that is based on the combination of the partitioned booking-limit policy and the generalized Nash game model. The results also show that this booking scheme is robust irrespective of which booking scheme the competitor takes.     

The capacity planning problem in make-to-order enterprises

This paper addresses the short-term capacity planning problem in a make-to-order (MTO) operation environment. A mathematical model is presented to aid an operations manager in an MTO environment to select a set of potential customer orders to maximize the operational profit such that all the selected orders are fulfilled by their deadline. With a given capacity limit on each source for each resource type, solving this model leads to an optimal capacity plan as required for the selected orders over a given (finite) planning horizon. The proposed model considers regular time, overtime, and outsourcing as the sources for each resource type. By applying this model to a small MTO operation, this paper demonstrates a contrast between maximal capacity utilization and optimal operational profit.     

The uncapacitated facility location problem with demand-dependent setup and service costs and customer-choice allocation

We consider a generalization of the uncapacitated facility location problem, where the setup cost for a facility and the price charged for service may depend on the number of customers patronizing the facility. Customers are represented by the nodes of the transportation network, and facilities can be located only at nodes; a customer selects a facility to patronize so as to minimize his (her) expenses (price for service + the part of transportation costs paid by the customer). We assume that transportation costs are paid partially by the service company and partially by customers. The objective is to choose locations for facilities and balanced prices so as to either minimize the expenses of the service company (the sum of the total setup cost and the total part of transportation costs paid by the company), or to maximize the total profit. A polynomial-time dynamic programming algorithm for the problem on a tree network is developed.     

Decomposing technical inefficiency using the principle of least action

In for-profit organizations, profit efficiency decomposition is considered important since estimates on profit drivers are of practical use to managers in their decision making. Profit efficiency is traditionally due to two sources – technical efficiency and allocative efficiency. The contribution of this paper is a novel decomposition of technical efficiency that could be more practical to use if the firm under evaluation really wants to achieve technical efficiency as soon as possible. For this purpose, we show how a new version of the Measure of Inefficiency Proportions (MIP), which seeks the minimization of the total technical effort by the assessed firm, is a lower bound of the value of technical inefficiency associated with the directional distance function. The targets provided by the new MIP could be beneficial for firms since it specifies how firms may become technically efficient simply by decreasing one input or increasing one output, suggesting that each firm should focus its effort on a specific dimension (input or output). This approach is operationalized in a data envelopment analysis framework and applied to a dataset of airlines.     

基于供应商视角的提前订货协调研究

本文针对一个供应商和零售商组成的供应链系统,主要研究零售商如何设计提前订货折扣来吸引顾客提前订货;而供应商如何根据市场需求的不确定性,设计零售商提前订货资金的付款时间等问题。在供应商-Stackelberg框架下,以期望利润为目标,建立了相应的决策模型。通过对模型的分析求解,给出了不同市场环境下供应商要求零售商支付提前订货资金的策略。最后,用算例验证了模型和理论分析的可行性。     

可加号的门诊预约能力分配问题

预约服务可以有效优化医院门诊就诊流程,针对我国患者预约意识不强和预约患者爽约率高的特点,本文研究患者需求量较高时可以增加号源的条件下,考虑加号和拒绝患者成本,以门诊收益期望最大为目标,匹配预约患者和现场挂号患者需求量的能力分配问题。证明了门诊收益期望函数的单峰性,给出了最优解满足的条件。通过大量数值实验分析不同参数对门诊能力分配方案的影响,结果表明两类患者需求量对能力分配方案有较大影响,可加号情况下能力分配方案对患者爽约更敏感。