Aircraft replacement scheduling: A dynamic programming approach

This study developed a stochastic dynamic programming model to optimize airline decisions regarding purchasing, leasing, or disposing of aircraft over time. Grey topological models with Markov-chain were employed to forecast passenger traffic and capture the randomness of the demand. The results show that severe demand fluctuations would drive the airline to lease rather than to purchase its aircrafts. This would allow greater flexibility in fleet management and allows for matching short-term variations in the demand. The results of this study provide a useful reference for airlines in their replacement decision-making procedure by taking into consideration the fluctuations in the market demand and the status of the aircraft.     

End-of-life aircraft treatment in the context of sustainable development,lean management,and global business

Dealing with retired aircraft taking into account the environmental, social, and economic impacts is emerging as an air transportation problem for the near future. The players involved in the problem wish to solve this challenge in a systematic way to benefit from the value extracted from the core activities of the end-of-life (EoL) aircraft treatment, decrease the environmental impacts, and at the same time maximize the social value. This paper proposes a holistic approach to EoL aircraft treatment considering lean management, sustainable development, and the global business environment. An integrated optimization framework is proposed to support decision-making at both the strategic and managerial levels. The flexibility of the framework makes it possible to compare different business models, dismantling strategies, and network structures that impact the efficiency, stability, and leanness of the recovery network. A solution methodology based on the joint application of fuzzy interactive approach and genetic algorithm is introduced. The application perspective and guidelines for pilot study are also provided. To the best of our knowledge, this is the first time that recovery of EoL aircraft is considered based on three aspects of sustainability, lean, and global business. Therefore, this study provides many promising perspectives in this context to enrich the literature of EoL aircraft as a new aviation industry challenge and opportunity.     

The impact of airport capacity constraints on future growth in the US air transportation system

This paper simulates airline strategic decision making and its impact on passenger demand, flight delays and aircraft emissions. Passenger flows, aircraft operations, flight delays and aircraft emissions are simulated for 22 airports in the US, under three airport capacity scenarios. The simulation results indicate that most system-wide implications for operations and environmental impact seem to be manageable, but local impacts at congested hub airports may be significant. The response of the air transportation system to avoid airports with high delays could significantly impact passenger demand and air traffic for these and directly dependent airports. The simulations also suggest that frequency competition effects could maintain flight frequencies at high levels, preventing a significant shift toward larger aircraft, which would otherwise reduce the impact of the capacity constraints.     

The implications of environmental costs on air passenger demand for different airline business models

Various environmental measures, including both regulations and fiscal instruments, have been used at airports globally to reduce the impacts of aircraft noise as well as aircraft engine emissions. Internationally, it is recognized that the costs of environmental and social externalities of air transport must be internalized and paid for by the aviation industry and its users. The use of noise related charges or taxes, which theoretically should be based on their respective social costs, has been proved to be effective at some European airports. This research aims to investigate the impacts of environmental costs, through environmental charges, on air passenger demand for different airline business models. The paper presents the mathematical models measuring the social costs of aircraft noise and engine emissions as a basis for setting up environmental charges. Six intra-European short-haul routes in two city pairs, namely London–Amsterdam and London–Paris, are selected for the empirical analysis. The environmental charges are then hypothetically applied to airlines with two different business models, full service carriers (British Airways and Air France-KLM) and low cost airlines (EasyJet). The results show that the potential percentages of demand reduction for both leisure and business passengers would be higher for Easyjet's markets, although with less environmental cost per passenger.     

From passenger growth to aircraft movements

Airlines are able to deal with passenger growth by either increasing the frequency or the aircraft size, which may entail different numbers of aircraft movements. Forecasting the latter is necessary for evaluating technologies, approaching future emissions or anticipating capacity constraints. Purpose of this paper is to forecast a typical fleet mix and the growth of aircraft movements on flight segments worldwide based on an assumed passenger growth. The methodology is implemented in a model called Forecast of Aircraft Movements. Basic approach is the assignment of each flight segment worldwide to a distance, passenger number and aircraft category. For each combination of distance and passenger numbers a typical fleet mix is defined. The forecasted worldwide growth of passenger demand and the empirically determined fleet mix is applied to all segments in order to derive a future scenario. Assuming a certain seat load factor, the frequency growth can be deduced from the aircraft movements generated for all segments. The paper includes a forecast for aircraft movements in a future scenario based on real schedule and passenger data and gives a detailed overview of the methodology and results considering airlines' behaviour.     

The cost of abatement options to reduce carbon emissions from Australian international flights

In 2012, a total of 13.1 million tonnes of carbon dioxide were emitted by 14 airlines while transporting 72 per cent of international passengers into and out of Australia in 2012. With passenger and cargo traffic growing at between five to six per cent annually from 2013 to 2033, acquiring more fuel efficient aircraft to both renew the existing fleet and to service growth has the greatest potential in reducing emissions over the next 20 years. Our analysis shows that implementing carbon dioxide emissions abatement options such as installing light weight seats, iPad electronic flight bags, winglets, washing aircraft engines and reducing the number of engines used during taxiing, all offer net financial savings when considered over 20 years. Acquiring new fuel efficient aircraft has the biggest impact on emissions reduction. Low interest loans and longer loan repayment periods may incentivise airlines to acquire more fuel efficient aircraft to service traffic growth but other complimentary incentives and penalties are required to influence airlines to replace their current fleet with more fuel efficient aircraft.     

铁路客运机车动态调度仿真研究

通过对铁路机车运用系统的调研,提出客运机车动态调度模式。考虑机车运用中的设备故障、机破等随机因素,建立机车运用动态调度仿真模型,确定模型约束条件。并以某客运机务段为例,对仿真结果进行分析,指出机车动态调度的实现条件,以及实现机车实时跟踪、减少设备投入和增强机务系统柔性等实施效果。     

Supply chain leading models of building charging stations: Leaders,subsidy policies,and cost sharing

Consumer willingness to pay for electric vehicles (EVs) is severely limited by their driving range. The expansion of a charging network could alleviate this dilemma. This paper focuses on determining whether the manufacturer or the dealer is more suitable to extend charging network. In scenario 1 (wholesale price is exogenous), M-Investing (the manufacturer invests on charging stations) better facilitates EV adoption at the early stage of EV market. By contrast, D-Investing (the dealer invests on charging stations) better facilitates the EV adoption when the market becomes mature. However, neither of the two investors have an incentive to offer building investment. In scenario 2 (wholesale price is a decision made by the manufacturer), M-Investing is consistently better than D-Investing in terms of facilitating EV adoption. The manufacturer is voluntary even with high building costs. In addition, we address two subsidy policies: producer subsidy and consumer subsidy, to determine which is more effective in facilitating EV adoption in M-Investing and D-Investing, respectively. Moreover, we extend our model by allowing cost sharing between the manufacturer and the dealer. We observe some cases in which the profit and the EV adoption level are improved.     

Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets

The selection of the appropriate aircraft can bring competitive advantages to airlines, however, there are a number of factors which introduce a degree of uncertainty to the selection process. By removing this uncertainty, airlines can increase their chances of achieving their long-term goals. New Multi-Criteria Decision Making (MCDM) methods provide decision-makers with a satisfactory solution for choosing suitable aircraft. Therefore, we focused on the multi-dimensional evaluation and selection of the most suitable commercial aircraft alternatives by using new MCDM method. This article provides decision support to airline planners on the selection of commercial aircraft under uncertainty. In the study, unlike other studies in the literature on aircraft selection, the model presented here uses an Interval Type-2 Fuzzy Analytical Hierarch Process (IT2FAHP) and Interval Type-2 Fuzzy Technique for Order Preference by Similarity to an Ideal Solution (IT2FTOPSIS) hybrid methods. The proposed model for aircraft selection allows commercial airlines to evaluate the aircraft in terms of specific criteria: economic performance, technical performance, and environmental impact, and, as a result, it helps decision makers select appropriate aircraft in an uncertain environment. In addition to use by commercial airlines, the methods in the study can also be applied to the selection of training aircraft, cargo aircraft and military aircraft. Our findings show that the Airbus A321neo is the most suitable commercial aircraft in terms of technical aspects, economic aspects and environmental aspects for airlines.     

Three-stage airline fleet planning model

One of the main factors affecting airline success is bringing supply and demand as closely together as possible. In order to achieve this goal, an airline needs to adopt an appropriate methodological approach for the fleet planning process. Selection of an aircraft for operating a defined route network is a key element which has a direct impact on the increase of an airline's profitability and on the reduction of an airline's costs. The objective of this paper is to develop a robust model for fleet planning that deals with both fleet size and fleet composition problems for airlines operating on short haul and medium haul routes. The three-stage model for fleet planning involves approximate fleet composition, fleet sizing and aircraft type selection based on fuzzy logic, heuristic and analytic approaches, and multi-criteria decision making, respectively. This model is exemplified with a hypothetical airline based at Belgrade Airport.     

Air cargo alliances and competition in passenger markets

This paper develops an oligopoly model to investigate the effect of an air cargo alliance on competition in passenger markets. We consider a model in which the partners, while continuing to offer their respective passenger services, jointly offer a new integrated cargo service by utilizing their passenger aircraft and routes. We find that such an alliance will likely increase the partners’ own outputs, while simultaneously decreasing its rivals’ outputs, in not only the cargo market but also the secondary passenger market. Furthermore, the alliance is likely to reduce passenger prices and increase total surplus.     

Measuring connectivity in the air freight industry

In this paper, we present an air transport connectivity model for air freight. For the purposes of this paper, connectivity is defined as all possible direct and indirect connections to or from an airport operated by wide-body aircraft, weighted for the quality of the connection in terms of transhipment and in-flight times. Using this model, we analyse the networks of seven European airports. Europe’s largest hub airports carry most air freight thanks to their extensive intercontinental passenger networks, while smaller airports with a strong focus on air freight carry large amounts of cargo on dedicated freighter aircraft. For air freight operations, the catchment area of an airport is much larger than it is for passenger services, as shipments are being trucked to their departure airport throughout all of mainland Europe. Since there are many airports sharing the same catchment area, potential competition for air freight is fierce. We found that well located regions between the four large European airports have access to large air freight networks, whilst regional air freight connectivity in northern and southern parts of Europe is substantially lower.     

The effect of airline service quality on passengers’ behavioural intentions: a Korean case study

This paper seeks to improving our understanding of air passengers’ decision-making processes by testing a conceptual model that considers service expectation, service perception, service value, passenger satisfaction, airline image, and behavioural intentions simultaneously. For this testing, path analysis via maximum likelihood estimator is applied to data collected from Korean international air passengers. Service value, passenger satisfaction, and airline image are each found to have a direct effect on air passengers’ decision-making processes.     

Theory and practice in aircraft financial evaluation

This paper explores the state of practice regarding aircraft financial evaluation. Traditional measures of aircraft economic viability, including direct operating cost comparison, ignore both the non-cash elements of costs, and the time value of money. Practitioners adopting more advanced techniques often go straight to the net present value calculation using an industry standard discount rate, ignoring critical problems such as estimating the cost of capital, quantifying the highly uncertain economic environment airlines face, and valuing the flexibility offered by manufacturer options and operating leasing. We propose taking advantage of the potential flexibility of the net present value approach by close attention to the choice of discount rates to flesh out investment/financing interactions, use of Monte Carlo analysis to quantify risk up front, and real options analysis to better understand the value of flexibility to aircraft operators.     

高速铁路柔性时刻表编制研究

随着新兴信息技术与交通的不断融合发展,需求响应型交通已成为未来交通发展的新模式,而柔性时刻表编制问题是决定这一新模式能否在高速铁路应用的关键问题之一。基于旅客预约条件下的需求响应型高速铁路柔性时刻表编制问题,提出完全柔性和部分柔性2种编制模式,构建同时考虑列车开行收益和旅客平均偏差时间的双层优化模型,设计模拟退火算法求解,以厦深高速铁路为例进行案例分析。研究结果表明,柔性时刻表编制模型求解得出的时刻表能够较好地匹配旅客预约的出行时间,有效满足旅客预约需求,提高运营收益,对未来需求响应型高速铁路具有一定参考价值。     

An analysis of the greenhouse gas emissions profile of airlines flying the Australian international market

International commercial flights (with the exception of flights between countries in European Union including Iceland, Norway and Liechtenstein) are currently not subject to greenhouse gas emission reduction regulation. To formulate effective and efficiency policy to manage greenhouse gas emissions from air transport, policy makers need to determine the emissions profiles of all airlines currently flying into their country or region. In this paper, we use 2012 data on airlines' aircraft characteristics, passenger load and cargo load (obtained from statistics reported by Australian Government Bureau of Infrastructure, Transport and Regional Economics) to estimate the volume and carbon efficiency on each international route flying to and from Australia. This is the first study to use actual passenger and cargo load data to determine the greenhouse gas (specifically CO₂) efficiency of airlines operating in the Australian international aviation market. Airlines' CO₂ emission profile is dependent on many factors including but not limited to the aircraft used, payload, route taken, weather conditions. Our results reveal that the airlines’ CO₂ emission profile is not only dependent on the aircraft used and the number of passengers but also the amount of cargo on each flight.     

Airline delay management problem with airport capacity constraints and priority decisions

This paper deals with the Airline Delay Management Problem (ADMP), which can be described as the task of dealing with daily airline operational delays and deciding whether to delay subsequent flights at a hub airport or to have them departing on time. An innovative integer linear programming approach is presented to the capacitated case of the ADMP and airport limitations in terms of bay availability, taxiway capacity and runway separation are incorporated to represent capacity constraints. Fuel cost, passenger compensation, and passenger inconvenience costs are included in the objective function. The decision variables include the re-timing of flight departures and arrivals, the use of the airport capacity over time and the rebooking of passengers in case of missed connections. To guarantee the linearity of the optimization model and fast computational times, a receding horizon modeling framework is adopted. The approach is applied to a case study using real operational and passenger data from an international hub-and-spoke carrier. The case study shows the capability of the linear model to deal with a complete day of operations within a few minutes. The results suggest that the proposed approach can lead to cost reductions of almost 30% during recovery, when compared with the solution from the airline. In addition, a sensitivity analysis is provided to investigate the impact of not including passenger inconvenience costs and of reducing runway capacity.     

Aircraft and passenger recovery during an aircraft’s unexpected unavailability

Airlines design their initial schedules under the assumption that all resources will be available on time and flights will operate as planned. However, some disruptions occur due to mechanical failures and unexpected delays of maintenance, making the aircraft unavailable for a certain period of time. These deviations from the initial plan result in high operational costs in addition to the serious inconveniences experienced by passengers. In order to handle aircraft and passenger recovery problems simultaneously, we work on integrated networks at which aircraft routings and passenger itineraries are superimposed. Consequently, we could calculate the actual profit and cancellation cost by evaluating each passenger itinerary while considering the seat capacity limitations. In our computational results, we use a daily schedule of a major U.S. airline and clearly demonstrate that there is an optimal trade-off between operating and passenger-related costs.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.