航班延误恢复调度的混合粒子群算法

为了优化航班延误恢复调度,考虑了航班延误的经济效益、社会影响和经济损失构成,定义了航线影响因子,构建了一种新的航班延误恢复调度模型,将局部搜索方法引入到粒子群算法中,提出了求解航班延误恢复调度问题的混合粒子群算法。计算结果表明:与先来先服务调度方法相比,混合粒子群算法可以减少航班延误损失4.2%,与基本粒子群算法和进化策略算法相比,混合粒子群算法平均可减少航班延误损失2.0%,随着航班延误恢复规模的增大,算法优势会更明显。     

基于市场进入博弈的高速铁路与航空竞争分析

提出了一个市场进入博弈模型来研究高铁和航空在中等运输距离上的竞争,重点考虑了票价、服务频率和乘客在不同交通方式之间因价格变动产生的转移等因素. 作为市场在位者,航空有允许和阻止两种策略,而高铁可以选择进入或者不进入市场,运用逆向归纳法求解出各种策略组合下航空和高铁的最佳策略,通过京沪高铁的实例展示了航空和高铁博弈的结果,给出了博弈双方的利润、票价、服务频率,以及在市场需求变动、机型变动和沉没成本变动条件下三者的变动情况. 结果表明,如果高铁的沉没成本不高并且市场需求充足,其最佳策略是进入市场,而航空的最佳策略是允许.     

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在航空运输市场竞争日益激烈的今天,客户资源成为航空公司最重要的资源;如何提高顾客的满意度并使之成为航空公司忠诚客户,是航空公司制胜的关键. 本文在顾客满意度指数测评模型ACSI、ECSI的基础上,构建了航空公司顾客满意度测评模型,设计了顾客满意度调查表,利用结构方程模型进行分析. 针对航空运输业的特点,本文去掉了欧美模型中的“感知价值”和“感知质量”,增加了“感知服务质量”这一新的变量,使得模型更具实用型和针对性;结合实际采样数据,通过满意度指标定量分析了各变量对顾客满意度的影响,得出了顾客“感知服务质量”对顾客满意影响最大,企业形象次之的结论,为航空公司战略调整指出了新的方向.     

A three-stage least squares approach to the analysis of airline strategies for aircraft size and airline frequency on the north Atlantic: an airline case study

In response to increasing demand, airlines may increase capacity by increasing the frequency of flights or they may choose to increase aircraft size. This may yield operating cost economies. If the airports they operate from are capacity constrained, they will be limited in the extent that they can change frequency which will limit their ability to compete with the number of frequencies offered. This article focuses on this trade-off and pays particular attention to the practices of a specific airline. Conclusions are offered on the impact of inter alia competition, changes in aircraft technology, 9/11 and the impact of slot constraints. It appears that changes in size are more important than frequency, which is consistent with the presence of slot constraints and there is a significant impact of competition. As the concentration of carriers increases, so aircraft size falls. 9/11 also has a significant impact on traffic whereas the introduction of the Boeing 777, as an illustration of a change in technology, does not.     

Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm

Abstract

This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations.     

基于malmquist指数的航空公司多级票价效率评价

为实现利润最大化,目前很多航空公司都实行多级票价体系,以获得更多的消费者剩余。引入数据包络分析法,利用malmquist指数,针对山东航空公司20条航线进行了多级票价的效率评价研究,通过实证发现,这20条航线中,有12条尚未达到DEA （date envelopment analysis ）有效,即多级票价体系尚需调整。同时,通过分解malmquist指数,可以从数据直观地看出影响航空公司多级票价体系效率的因素,其中9条是由于多级票价结构原因,7条是由于票价价位原因。     

基于旅客步行距离的停机位均衡优化指派建模

针对机场停机位指派问题,从旅客服务质量角度出发,以缩短机场旅客步行总距离和均衡各航空公司的旅客平均步行距离为目标,建立停机位指派优化模型.采用Lingo软件对国内某大型机场的停机位指派进行仿真验证.结果表明：旅客步行总距离会影响航空公司间公平性;与随机指派相比较,该模型能同时缩短旅客步行总距离和提高航空公司公平性.     

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针对航空公司安全系统风险评价中存在的不确定性因素，将证据理论引入航空公司安全系统的风险评价中，以解决评价过程中所遇到的不确定性问题，建立了航空公司安全系统风险评价指标体系，给出了基于证据理论的评价模型和算法，通过实例计算，验证了该方法能较好地解决航空公司安全系统风险评价过程中所遇到的不确定性问题。     

Future electricity demand from battery‐powered vehicles

An important decision faced by airline schedulers is how to adapt the flight schedule and aircraft assignment to unforeseen perturbations in an established schedule. In the face of unforeseen aircraft delays, schedulers have to decide which flights to delay, and when delays become excessive, which to cancel. Current scheduling models deal with simple decision problems of delay or cancellation, but not with both simultaneously. But in practice the optimal decision may involve results from the integration of both flight cancellations and delays. In Part I of this paper, a quadratic programming model for the integration decision problem is given. The model can formulate the integration of flight cancellations and delays as well as some special cases, such as the ferrying of surplus aircraft and the possibility of swapping different types of aircraft. In this paper, based on the special structure of the model, an effective algorithm is presented, sufficient computational experiments are conducted and some results are reported. These show that we can expect to obtain a sufficiently good solution in terms of reasonable CPU time.