A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling,with consideration of fleet assignment problem

One of the most important airline's products is to determine the aircraft routing and scheduling and fleet assignment. The key input data of this problem is the traffic forecasting and allocation that forecasts traffic on each flight leg. The complexity of this problem is to define the connecting flights when passengers should change the aircraft to reach the final destination. Moreover, as there exists various types of uncertainties during the flights, finding a solution which is able to absorb these uncertainties is invaluable. In this paper, a new robust mixed integer mathematical model for the integrated aircraft routing and scheduling, with consideration of fleet assignment problem is proposed. Then to find good solutions for large-scale problems in a rational amount of time, a heuristic algorithm based on the Simulated Annealing (SA) is introduced. In addition, some examples are randomly generated and the proposed heuristic algorithm is validated by comparing the results with the optimum solutions. The effects of robust vs non-robust solutions are examined, and finally, a hybrid algorithm is generated which results in more effective solution in comparison with SA, and Particle Swarm Optimization (PSO).     

A hybrid fuzzy MCDM approach for mitigating airport congestion: A case in Ninoy Aquino International Airport

In this paper, we introduce the application of an integrated fuzzy multi-criteria decision-making (MCDM) model to mitigate airport congestion which affects the on-time performance of airlines, operational reputation of airports, and air travel experience of passengers. In a classical approach, when congestion occurs at the destination airport while the aircraft is en-route, an air traffic flow management action is prompted for implementation. In selecting the most suitable action in the event of airport congestion, the decision must reflect the multiple criteria nature of the problem as well as the uncertainty and vagueness associated with the decision-making process; thus, an integrated fuzzy MCDM is adopted. The applicability of the proposed approach is demonstrated in a case study at Ninoy Aquino International Airport. It is found that stakeholders of the commercial aviation industry favored to apply rerouting, among other actions, as this satisfies aviation safety as the most prioritized criterion.     

Management of airport congestion through slot allocation

The lack of airport slots (the time allocated for an aircraft to land or take off), particularly at airports which experience congestion, have reached unmanageable proportions in recent years. The International Civil Aviation Organization (ICAO) records that, by the end of 1997, there were 132 slot controlled international airports. The World of Civil Aviation, 1997–2000. ICAO Circular 273-AT/113, p. 12 (118 year round and 14 during peak seasons). Between 1989 and 1998 the reported number of commercial aircraft in service increased by about 60% from 11,253 to 18,139 aircraft. In 1998, 1463 jet aircraft were ordered, compared with 1309 in 1997, and 929 were delivered compared with 674 aircraft in 1997. In 1998, the total scheduled traffic carried by airlines of the 185 Contracting States of ICAO amounted to a total of about 1462 million passengers and about 26 million tonnes of freight. These figures¹ are reflective of the rapidly increasing frequency of aircraft movements at airports, calling for drastic management of airport capacity. To cope with the demand, airlines are forming strategic alliances with themselves by utilizing such commercial tools as franchising, leasing and interchange of aircraft. The management of airport capacity through slot allocation is a critical consideration for the world aviation community. This article analyses the problem and discusses various issues related thereto.     

Control-based optimization approach for aircraft scheduling in a terminal area with alternative arrival routes

This paper presents an optimization approach for dynamically scheduling aircraft operations and supporting air traffic controllers in both determining and implementing operationally feasible landing and departure times at an airport. The mixed integer linear programming model proposed incorporates air traffic control infrastructure in terms of route network, introduces the concept of alternative approach routes and is designed to generate an output that can be converted into effective advisories for executable flight commands. It shows reasonable computational times for obtaining the optimal solution and delay reductions of up to 35% with practical size instances from Sao Paulo/Guarulhos International Airport.     

A systematic approach to assess the effectiveness of airport noise mitigation strategies

Regional airports are often located very close to the urban area they serve and the increasing traffic rate that many of them have experienced in the last years has produced several impacts on the communities living close to the airport area, mainly aviation noise. If not properly managed, noise impacts produced by airport operations can cut down significantly the development of airport air traffic with direct effects on the economic and territorial systems. Aeronautical noise has greatly reduced in the last decade, due to aircraft design technological improvements and more severe regulations. However, the noise reduction during a single event does not make the issue of the airport location – and then the whole noise impact – less significant. This paper proposes an assessment process to evaluate the effects of actions adopted to reduce airport noise impacts on populated areas. Both airport-related factors – such as number of take-off; day-evening-night distributions of movements; aircraft type; flying paths – and land-use characteristics have been considered and combined in a density index that synthesizes the impacts of airport noise on the territory. The assessment process has been tested on a real case, the airport of Bologna in Northern Italy. The predicted results, compared with available real data for the test case, are significant and encourage the use of the proposed assessment process as decision support system for the airport management.     

Airport traffic complexity and environment efficiency metrics for evaluation of ATM measures

For a given (current or planned) traffic demand, different air traffic management measures could result in different airport traffic complexity and efficiency. This paper presents the research on the relationship between airport traffic complexity and time and environmental efficiency for different air traffic control (ATC) tactics applied to the given or planned airport layout. Emphasis is placed on the evaluation of airport traffic complexity, aircraft fuel consumption, gas emissions and time efficiency for different ATC tactics and/or airport airfield layouts. For busy airports during peak hours, arrival queuing delays, taxi-in, taxi-out times and departure queuing delays increase, which induces additional unnecessary fuel consumption, gas emission and time inefficiency. In order to find a tool which could indicate potential delay generators, a measure of airport traffic complexity – called Dynamic Complexity is proposed. Experiments were performed for airports with different airfield layouts, for different traffic demands and ATC applied tactics using SIMMOD simulation model. Traffic situations were analyzed and delays were measured. The values of airport traffic complexity, fuel consumption and gas emissions were also determined. A comparative analysis of the results show: first, the proposed airport traffic complexity metric quite satisfactorily reflects the influence of traffic characteristics upon the environmental state of the system, and second, different ATM strategic and tactical measures (airport airfield infrastructure development and applied ATC tactics) could significantly reduce traffic complexity and increase time and environmental efficiency at the airport.     

A heuristic approach for solving an integrated gate reassignment and taxi scheduling problem

Capacity limitation of airport ground operation is one of the major limiting factors in air traffic operation. The congestion on the gate and taxiway causes severe delay and propagate effect on the flight schedule. This paper considers the problem of integrated gate reassignment and taxiway scheduling, in which complex constraints related to runway restriction, gate allocation and taxiway conflict are all incorporated when determining the schedule. To solve this problem, we propose a novel heuristic approach. First, all possible aircraft schedules are enumerated by disretizing the waiting time along the path. Then, the cost is evaluated for each schedule and the conflict detection is conducted to generate constraint sets. Finally, we propose a set partition model, in which each decision variable denotes a candidate schedule that takes into account the possible constraints when generated. This method is compared with a sequential method that solves gate reassignment and taxiway scheduling problem separately. Computational results highlight the strength of our method.     

Airport slot allocation: a time for change?

The increasing imbalance between airport capacity and traffic resulted in exceptional congestion and delays drawing the attention of aviation policy makers towards airport demand management for the allocation of scarce airport slots. Attempts to bring forward airport demand management measures in the form of airport slot allocation were not widely adopted and have not flourished in practice. This paper aims: (i) to apply a methodological framework for the selection of the most suitable slot allocation strategy for various types of airports, (ii) to explore potential impacts such that measures or strategies can bring about, and (iii) to assess the suitability of the existing airport pricing scheme and the potential implementation of a new policy regime aiming to bridge the gap between growing traffic and scarce airport capacity.     

Methods of air traffic management in the airport area including the environmental factor

In the modern approach to air traffic management (ATM), issues related to air quality and climate protection have led to the introduction of a growing number of new restrictions instead of having these issues be the objectives of actions taken. The aim of the study was to investigate whether it is possible to improve air quality while controlling pollution emission by introducing changes in the organization of air traffic control at the airport. For this purpose, mathematical models of emissions were created. These concern the movement of aircraft near the airport and emission of carbon dioxide and the spread of human health related substances emitted from a landing airplane's engine. The first case refers to the possibility of using different arrival procedures. The second case was to adapt the Pasquill formula by treating landing aircraft as a sequence of point-source emissions. As a result of applying the designed models and software tools, it was proven that both a change in the arrival trajectory and a change of the runway can contribute to a reduction of CO₂ emission into the atmosphere. The emission maps created for different aircraft approach profiles show the ability to control the local concentration of harmful emissions. The study clearly shows that the current approach of maximizing throughput is not beneficial to air quality. ATM services should consider the use of other variants of air traffic organization, particularly during periods of reduced traffic.     

Estimating the marginal costs of airport operation using multivariate time series models with correlated error terms

This paper explores insights about marginal airport costs that can be gained by analysing labour inputs and their variability. Based on hourly cost and traffic data for the airport of Helsinki, a multivariate time series approach is used incorporating correlated error terms to account for random shocks such as delays. We found for most airport services a linear relationship between labour input and aircraft movements, except for producing passenger services for international departing flights where a cubic cost relationship was estimated. The findings are comparable with earlier studies for US airports.     

A tool to support resource allocation at small-to-medium seasonal airports

During a few months of the year seasonal airports face the challenging task of maintaining service quality while dealing with heavy traffic, often being pushed to operate on the limit of their available capacity. Under such circumstances, efficient allocation and timely reallocation of physical and human resources is what keeps the service quality of airports at an acceptable level.The paper describes a tool to support allocation of the physical resources, developed for particular seasonal airport falling in the range 1–5 million annual passengers. The tool is designed to work with the traffic schedule – to check it against existing constraints imposed by area, and to assign the appropriate alert if any of the constraints are violated. Thus, the tool provides airport planners with a clear overview of the traffic situation. Its main function is to allow airport planners to check the effects of different actions to resolve particular constraints violations on the overall situation, before making the final decision. Due to non-disclosure agreement, the tool and its features are presented in the paper on somewhat modified example.     

Managing turnaround performance through Collaborative Decision Making

The purpose of this paper is to explore turnaround performance as a resultant from both Collaborative Decision Making (CDM) processes and collaborative measures. This paper presents how CDM operates in the Turnaround Process (TAP) to propose a new method for managing the collaborative turnaround performance of all actors by predicting the most critical indicators. To achieve this, data from a CDM airport is used. Sample data of 6500 observations, taken from turnaround movements handled in 2014 at Madrid-Barajas Airport, were obtained from three separate databases and analyzed separately (in three databases). To predict turnaround performance, this paper also introduces a predictor dependent variable called “star values” as a measure of minimal delay conditions in order to predict time performance. The analysis shows that the proposed method unveils a new approach in determining how collaborative performance can be measured in the TAP and the predicted key performance indicators, which shows variations in the predicted CDM indicators. Results challenge managers and policymakers to find which improvements can be enacted for better usage of airport infrastructures and resources for optimum use as well as enhanced TAP. In terms of theory use and extension, the study reveals how CDM is an essential element in the literature on air traffic management.     

Regional public support to airlines and airports: An unsolved puzzle

This paper proposes a structural model to explain the motivation of regional public authorities to arrange marketing agreements for route and traffic development. Furthermore, using data from Spanish airports, we empirically test this model obtaining the demand function according to the preferences of public authorities. The results show that the public budget, airport’s attributes or intermodal competition affect to the demand for aircraft operations of regional public agencies. Finally, we propose an empirical method to determine the market power of airlines within these marketing agreements in a particular airport or route.     

Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration

The Federal Aviation Administration has several tools in its arsenal to manage traffic flows. However, it is very difficult to assess with certainty the impact of traffic flow management procedures such as Time-Based Flow Management (TBFM) or Traffic Management Initiatives (TMI) on airport performance because operational data are not readily available to analysts. This study uses the case of Fort Lauderdale–Hollywood International Airport (FLL) where traffic flow management procedures have been implemented to manage a reduction of airport capacity due to runway constructions. Based on an Autoregressive Conditional Duration (ACD) model, the analysis shows that the use of traffic flow management procedures contributed to reducing the volatility of interarrival duration whether separation relies on time-metering (TBFM) or distance between aircraft (TMI). The lessons learned from this case study may have important implications for airports whose available capacity is severely constrained.     

The impact of low-cost carriers on airport choice in the US: A case study of the Washington–Baltimore region

Previous research has shown that low-cost carriers (LCCs) may stimulate traffic at an airport by offering low fares. Using passenger survey data from the Washington–Baltimore region’s three airports, we find that the benefits of LCCs to airports extend beyond the traffic generated directly by the LCCs through their low fares. In addition, we find that the mere presence of an LCC at an airport can attract passengers, even to competing carriers. These “halo effects” from LCC presence increase the significance to airport managers of attracting LCCs in order to generate passenger demand.     

Modelling of aircraft rotation in a multiple airport environment

The objective of this paper is to develop a simulation model to simulate aircraft rotation in a multiple airport environment. The developed aircraft rotation model (AR model) consists of two sub-models, namely the aircraft turnaround model, which describes the operation of aircraft turnaround activities at an airport and the Enroute model, which simulates the enroute flight time of an aircraft in the airspace between two airports. Delays due to operational disruptions from aircraft turnaround activities are modelled by stochastic variables in the aircraft turnaround model. Uncertainties from schedule punctuality are modelled by probability density functions in the Enroute model. The proposed aircraft rotation model is employed to carry out a case study by using real schedule and punctuality data from a European schedule airline. Simulation results when compared with observation data validate the effectiveness of the aircraft rotation model. The proposed model is also found suitable for airlines to serve as a schedule planning and analysis tool.     

Analyzing tactical control strategies for aircraft arrivals at an airport using a queuing model

This paper proposes to analyze control strategies for arrival air traffic at an airport using a classical queuing model. The parameters of our model are estimated by means of a data-driven analysis of two years of radar tracks and flight plans for arrival flights at Tokyo International Airport from 2016 to 2017. Our results show that increasing the capacity with one or two more aircraft in the airspace up to 60 NM around the airport significantly mitigates arrival delays, even when assuming future, increased arrival traffic volumes. The outcomes of this study provide insights into the effectiveness of arrival control strategies and are seen as a means to recommend scenarios to be further analyzed with human-in-the-loop simulations.     

Intermodal integration in air transportation: status quo, motives and future developments

Soaring air traffic, increasing urban expansion and airports operating at full capacity are reasons that have caused a discussion about improvements in airport landside access systems. One approach to better match customer demands and address airport congestion is to facilitate the intermodal integration of airports. Building on a survey on intermodal passenger air transportation, we elaborate on the current and future situation at major airports. Our findings indicate a high modal concentration and dependence on individual access modes. However, while airport managers intend to reduce the share of these modes, they plan to increase that of high-occupancy airport access modes. We analyze the underlying motives that cause airports to extend their connections to surface infrastructure. In a case study, we assess an intermodal best practice solution for the integration of air and rail.     

A methodology for establishing operational standards of airport passenger terminals

This paper discusses a methodology for establishing the operational standards of service performance of airport passenger terminals using a perception–response model. The proposed approach is defined by the graphical representation of passengers’ collective attitudes towards the range of operational service at an airport passenger terminal. It adopts new concepts to establish service standards through a special survey to better interpret terminal operations and service level at each facility. It is expressed in terms of passengers’ perception of various service levels and their response to the respective service conditions. The methodology may provide practical service standards of airport terminals and prove to be a practical and convenient technique to airport planners, designers, consultants, operators, and airport managers.     

Factors influencing cargo agents choice of operations in Abuja airport,Nigeria

The ability of an airport to attract traffic can vary within a multi-airport model of operation and highly competitive environment. This study is an effort to examine the factors that cargo agents rank as most important in their choice of Abuja airport cargo transhipment operations. A questionnaire survey was conducted on a random sample of members of the Association of Nigeria Customs Licensed Agents (ANCLA) at Abuja airport for primary data collection. The study employed a combination of Factor Analysis (FA) and Multiple Linear Regression (MLR) to analyse the data collected. The results of the factor loadings indicate airport capacity, airport charges and customs efficiency as the most significant factors that agents consider in their choice of handling cargo through Abuja airport. The three variables were found to have a high correlation relationship (R = 0.802) with the dependent variable of airport choice after subjecting it to regression analysis. This serves as information to airport managers for the airport planning of capacity in cargo operations within multi-airport country such as Nigeria.