考虑地区因素的航空收益管理

对于中国这样一个因地区经济水平不同而造成地区消费差异极度巨大的国家,航空公司应该怎样设置卖票策略使自己的各个航班的效用最大,传统的方法是票价系统因地而异,但这种方法有很大的随意性,并且对订票系统改变较大,操作成本高。本文将采用一个新的方法讨论该问题。首先,引进一个反映地区消费水平的参数,简称地区因子。然后结合一个单阶段航班,建立考虑地区因子的随机动态模型,同时证明了与效用函数相关的一些性质:比例边际效用函数是分别关于时间,待订票数和地区因子的单调增加函数。基于这些性质,对连接不同地域的航班,我们只要调整地区因子,再采用阀值控制策略就能使航班的效用最大且空置率得到有效抑制。最后,给出了一个实例。     

航空公司超额订票的收益分析

研究了航空公司超额预订机票的收益问题 .通过建立多等级票价模型 ,分别对一个航班和两个航班超额订票的收益进行研究 ,并讨论收益对预订票数、未到乘客数等参量的敏感性 .     

买票的学问

五一小长假,我们一家三口来到探险王国准备进行一次探险之旅。
　　到了大门口,我便拉着爸爸奔向售票窗口,只见窗户上醒目标着：成人票160元/人,儿童票80元/人。爸爸从衣袋里掏出皮夹,边拿钱边问我：“算算我们应该付多少钱？”我不假思索地回答：“160+160+80=400（元）。”“口算能力还不错嘛！”爸爸夸奖我。“哇！400元好贵啊！”我张大嘴巴大叫着。一旁的妈妈摸出手机发话了：“等一下,我看看网上订票会不会便宜些。”“你妈就是这样,就喜欢网购。”爸爸小声嘀咕。妈妈没理会爸爸,专注地滑着手机。     

基于粒子群算法的航班舱位控制研究

首先介绍了收益管理提出的背景思想,在对航班收益管理基本概念作简要阐述的情况下,给出了期望边际座位收入理论.提出了在北京到上海的单航程航段下,航空公司会提供出发时间不同但航程相同的连续两个航班.旅客在没能购买到期望的航班舱位时,会以一定的概率选择购买下一航班的机票或者取消订票,改乘其他交通运输工具.旅客对于某一航班的座位需求主要由固有需求和上一航班需求的转移两部分构成.基于这样的角度建立了两航班机票预售模型,不考虑动态订座,no-show和超售等情况,并利用算法对模型进行了求解和分析.最后得出结论当航班票价等级数量较少时,为高票价等级安排较多数量座位可提高航班收入.而当航班票价等级数量比较多时,为低票价等级多安排一些座位可为航班提高收入.     

基于承诺交货期的两阶通用件库存模型

在一个两阶段生产系统中,针对第二阶段应用单通用件的情况,引入承诺交货期因素,分别建立了第一阶段无通用件、单通用件、双通用件库存模型,考查了承诺交货期对通用件库存模型总成本的影响,分析了三类模型相应的最优库存水平。通过算例,说明了在一个第二阶段采用单通用件的两阶段生产系统中,当通用件与非通用件的单位采购成本相同时,并非第一阶段使用越多的通用件,总成本就越低。     

考虑消费者有限理性退货决策的两阶段C2B电子商务供应链回购策略优化研究

文章研究两阶段C2B电子商务交易,重点研究有限理性的消费者的退货行为给供应链成员带来的影响,并进一步研究前一阶段中的退货行为对后阶段的销售影响,结果表明两阶段的最优退货抵偿不同,基于此对两阶段销售进行了协调研究,研究表明,制造商可以调节退货后的回购价格使两阶段销售得以协调。最后,运用数值算例验证了相关结论。     

状态离散的确定性多阶段群体决策的满意策略

为了求解状态离散的确定性多阶段群体决策问题,建立了多阶段群体决策模型,定义了群体Pareto最优策略、群体满意策略等概念,依据Bellman最优性原理,提出了多阶段群体决策问题的逆向递推算法,并通过引入偏好关系,得到了各阶段的子过程群体满意策略以及全过程群体满意策略,最后给出了一个计算实例．     

产品回收逆向物流网络设计问题的两阶段启发式算法

针对产品回收逆向物流网络设计问题,设计了一种嵌套了模拟退火算法的两阶段启发式算法。第一阶段确定回收点的选址-分配-存储的联合决策;第二阶段确定回收中心的选址-运输的联合决策,两个阶段相互迭代,从而实现最优解的搜索。通过与遗传算法比较,证明了两阶段启发式算法是一种有效的算法。     

非线性年龄依赖细胞分裂模型

讨论非线性年龄依赖带两阶段结构的细胞分裂模型,建立了增殖阶段和休眠阶段的年龄结构的等价模型,并证明了模型的解的存在唯一性.     

利用变式教学强化学生对概念本质的理解——以“无穷等比数列各项和”的概念教学为例

数学知识大部分都是程序性知识,在经历了知识的陈述性阶段学习后,需要通过意识控制的练习达到熟练程度,从而过渡到自动化阶段。概念的简单描述,帮助学生完成了陈述性阶段学习．通过变式教学,可以从不同角度揭示概念的本质,帮助学生经历意识控制阶段的练习,从而掌握概念的本质。     

A heuristic approach based on shortest path problems for integrated flight,aircraft, and passenger rescheduling under disruptions

In this paper, we present a heuristic method to solve an airline disruption management problem arising from the ROADEF 2009 challenge. Disruptions perturb an initial flight plan such that some passengers cannot start or conclude their planned trip. The developed algorithm considers passengers and aircraft with the same priority by reassigning passengers and by creating a limited number of flights. The aim is to minimize the cost induced for the airline by the recovery from the disruptions. The algorithm is tested on real-life-based data, as well as on large-scale instances and ranks among the best methods proposed to the challenge in terms of quality, while being efficient in terms of computation time.     

Modeling and Solving an Airline Schedule Generation Problem

Since opening a new flight connection or closing an existing flight has a great impact on the revenues of an airline, the generation of the flight schedule is one of the fundamental problems in airline planning processes.In this paper we concentrate on a special case of the problem which arises at charter companies. In contrast to airlines operating on regular schedules, the market for charter airlines is well-known and the schedule is allowed to change completely from period to period. Thus, precise adjustments to the demands of the market have a great potential for minimizing operating costs.We present a capacitated network design model and propose a combined branch-and-cut approach to solve this airline schedule generation problem. To tighten the linear relaxation bound, we add cutting planes which adjust the number of aircraft and the spill of passengers to the demand on each itinerary.For real-world problems from a large European charter airline we obtain solutions within a very few percent of optimality with running times in the order of minutes on a customary personal computer for most of the data sets.     

A model for designing the meteorologically most reliable airline schedule

Due to meteorological conditions certain airports in some regions have to be frequently closed during winter months. An immediate consequence is an increase in the number of cancelled flights, which is a disruption of airline schedules on the overall transportation network. In this paper a research concerning the reliability of airline scheduling as related to meteorological conditions is conducted and an indicator for quantifying the adaptability of airline schedules to meteorological conditions is proposed. A heuristic algorithm for minimizing the number of needed aircraft for given traffic volume is also presented. In case where more than one solution with the same number of engaged aircraft is possible the solution chosen is the one with the minimum number of passengers whose flights are expected to be cancelled on account of meteorological conditions. The proposed algorithm is illustrated by an appropriate numerical example.     

A benders decomposition approach for an integrated airline schedule design and fleet assignment problem with flight retiming, schedule balance, and demand recapture

The airline’s ability to offer flight schedules that provide service to passengers at desired times in competitive markets, while matching demand with an aircraft fleet of suitable size and composition, can significantly impact its profits. In this spirit, optional flight legs can be considered to construct a profitable schedule by optimally selecting among such alternatives in concert with assigning the available aircraft fleet to all the scheduled legs. Examining itinerary-based demands as well as multiple fare-classes can effectively capture network effects and realistic demand patterns. In addition, allowing flexibility on the departure times of scheduled flight legs can increase connection opportunities for passengers, hence yielding robust schedules while saving fleet assignment costs within the framework of an integrated model. Airlines can also capture an adequate market share by balancing flight schedules throughout the day, and recapture considerations can contribute to more realistic accepted demand realizations. We therefore propose in this paper a model that integrates the schedule design and fleet assignment processes while considering flexible flight times, schedule balance, and recapture issues, along with optional legs, path/itinerary-based demands, and multiple fare-classes. A polyhedral analysis is conducted to generate several classes of valid inequalities, which are used along with suitable separation routines to tighten the model representation. Solution approaches are designed by applying Benders decomposition method to the resulting tightened model, and computational results are presented using real data obtained from United Airlines to demonstrate the efficacy of the proposed procedures.     

乘客策略行为下考虑需求学习的航空客运动态定价策略研究

研究航空公司在需求学习下的动态定价策略。通过假设乘客到达率不确定以及具有策略等待行为,运用贝叶斯理论和博弈论对航空公司需求学习下的多周期动态定价问题进行建模,探讨了机票最优定价策略的充分条件,并通过分析航空公司收益函数的性质,得到了最优定价随时间和已出售机票数量的变化趋势。最后应用算例分析了需求学习的效果,得出:需求学习能够缓解需求不确定带来的损失,但不能完全消除;乘客策略程度越大,需求学习效果越明显。     

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.     

基于多目标规划的飞机路径恢复最优化算法研究

本文针对同一机场中同机型的多架飞机受到干扰后, 飞机路径恢复的多目标最优化问题进行研究。首先根据航空公司实际航班调整的常用原则和航班干扰管理的基本思想, 基于连接网络建立多目标规划模型, 其中两个目标按照优先级排列:第一个目标为最小化航班的最大延误时间, 第二个目标为最小化参与交换的飞机数量。然后根据该问题的航班波结构特点, 结合求解多目标规划的分层序列法, 分析优化问题的若干最优性质, 并基于快速排序算法和最小费用路算法设计出多项式算法。最后用算例验证了算法的有效性。该研究结果可以为航空公司减少航班延误提供理论和技术支持。     

A network model for airport common use check-in counter assignments

The purpose of flight to check-in counter assignments is to assign each flight to specific check-in counters where the airline will provide passenger check-in services. The number of common use check-in counters required for daily operations is an important issue closely related to the airport's level of service and system performance. In this study, a new network model is developed for the optimization of common use check-in counter assignments. The goal is to minimize the number of counters required for daily operations. Numerical tests are performed on data for a major Taiwan airport. The obtained results show that the model performs well.     

基于改进RFM模型对民航客户的细分研究

近年来航空公司将客户分成不同的群体为了给客户提供差异化服务和有针对性的营销.现有传统的客户细分RFM模型由于存在缺乏科学的指标建立,已无法准确和完整的描述实际情况中客户的细分结果,根据民航客户价值的特点,在传统客户细分的RFM模型上进行改进,创建LRFMC模型,对某航空公司客户采用数据挖掘K-means算法进行聚类分析...     

Driving while intoxicated (DWI) convictions and job-related flying performance—a study of commercial air safety

This paper is a report on the relationship between driving while intoxicated (DWI) convictions and job-related flying performance. The data, obtained by the Federal Aviation Administration, focuses on commercial air accidents and incidents in the years 1986–1992. Pilot-error accidents were modelled using logistic regression with age, experience (total flying hours), risk exposure (recent flying hours) and employer (major/non-major) as the independent variables. This study provides empirical evidence that job-related flying performance differs significantly between airline pilots with and without DWI convictions. It also suggests that passengers on a commercial flight flown by a pilot with DWI(s) may incur an increased accident risk. DWI background checks may be an effective method for improving commercial air safety if used with appropriate follow-up actions.