The importance of considering pushback time and arrivals when routing departures on the ground at airports

With the constant increase in air traffic, airports are facing capacity problems. Many airports are increasingly interested in utilising optimisation methods for specific airport processes. However, many such processes do happen in parallel, and maximising the potential benefits will require a complex optimisation model. A model which considers multiple processes simultaneously and the detailed complexities of the processes, rather than using more abstract models. This paper investigates how the arriving aircraft can affect the routing process and whether the pushback process can result into different types of delays. Furthermore, aircraft are routed backwards, starting from the destination in order to be at the runway on time and to respect the departure sequence. After testing our model with and without the arriving aircraft we found that arriving aircraft can indeed produce a lot of delays. Such delays would otherwise pass unnoticed as they result to departing aircraft choose different paths or pushback earlier so they be at the runway on time. Having an accurate model for the pushback process is important in order to understand in depth how the pushback process affects the other processes that happen in parallel. Furthermore, it led to more accurate and realistic model, which may assist the decision making process for ground movement operations and thereby help airports increase their capacity and become more environmentally friendly

The importance of considering pushback time and arrivals when routing departures on the ground at airports

With the constant increase in air traffic, airports are facing capacity problems. Many airports are increasingly interested in utilising optimisation methods for specific airport processes. However, many such processes do happen in parallel, and maximising the potential benefits will require a complex optimisation model. A model which considers multiple processes simultaneously and the detailed complexities of the processes, rather than using more abstract models. This paper investigates how the arriving aircraft can affect the routing process and whether the pushback process can result into different types of delays. Furthermore, aircraft are routed backwards, starting from the destination in order to be at the runway on time and to respect the departure sequence. After testing our model with and without the arriving aircraft we found that arriving aircraft can indeed produce a lot of delays. Such delays would otherwise pass unnoticed as they result to departing aircraft choose different paths or pushback earlier so they be at the runway on time. Having an accurate model for the pushback process is important in order to understand in depth how the pushback process affects the other processes that happen in parallel. Furthermore, it led to more accurate and realistic model, which may assist the decision making process for ground movement operations and thereby help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

Taxiway Aircraft Traffic Scheduling: A Model and Solution Algorithms

With the drastic increase in the demand for air travel, taxiway aircraft traffic scheduling is becoming increasingly important in managing air traffic. In order to reduce traffic congestion on taxiways, this thesis proposes a tool for air traffic controllers to use in decision making: a taxiway air traffic model developed using Mixed Integer Programming (MIP) that can be applied to a rolling time horizon. The objective of this model is to minimize the total taxi time, and the output is a schedule and route for each aircraft. This MIP model assumes that only the origin and destination of each aircraft is fixed; due to some uncertain factors in the air arrival and departure process, it allows for the departure time and arrival time to vary within a certain time window. This MIP model features aircraft type, and also incorporates runway crossings and runway separations. The model is programmed using C++ and Solved in CPLEX 12.1. Runways 26R and 26L of George Bush International Airport are used to find solutions. The author presents a rolling horizon method by dividing the large scheduling issue into smaller time interval problems according to the scheduled times of departure or arrival. A bound is also proposed based on the discretized time interval problems. By using partial data from George Bush International Airport (IAH), solutions are obtained. The results are compared with the bound and show fairly high optimality. Compared with the previous research, this thesis presents a model with more flexibility by considering different operations. By using the rolling horizon method, the problem is broken into smaller units that can be solved efficiently without losing much optimality

Benders' decomposition algorithm to solve bi-level bi-objective scheduling of aircrafts and gate assignment under uncertainty

Abstract Management and scheduling of flights and assignment of gates to aircraft play a significant role in improving the procedure of the airport, due to the growing number of flights, decreasing the flight times. This research addresses assigning and scheduling of runways and gates in the main airport simultaneously. Moreover, this research considers the unavailability of runway's constraint and the uncertain parameters relating to both areas of runway and gate assignment. The proposed model is formulated as a comprehensive bi-level bi-objective problem.The leader's objective function minimizes the total waiting time for runways and gates for all aircrafts based on their importance coefficient. Meanwhile, the total distance traveled by all passengers in the airport terminal is minimized by a follower's objective function. To solve the proposed model, the decomposition approach based on Benders' decomposition method is applied. Empirical data are used to show the validation and application of our model. A comparison shows the effectiveness of the proposed model and its significant impact on cost decreasing

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

A chance-constrained programming model for airport ground movement optimisation with taxi time uncertainties

Airport ground movement remains a major bottleneck for air traffic management. Existing approaches have developed several routing allocation methods to address this problem, in which the taxi time traversing each segment of the taxiways is fixed. However, taxi time is typically difficult to estimate in advance, since its uncertainties are inherent in the airport ground movement optimisation due to various unmodelled and unpredictable factors. To address the optimisation of taxi time under uncertainty, we introduce a chance-constrained programming model with sample approximation, in which a set of scenarios is generated in accordance with taxi time distributions. A modified sequential quickest path searching algorithm with local heuristic is then designed to minimise the entire taxi time. Working with real-world data at an international airport, we compare our proposed method with the state-of-the-art algorithms. Extensive simulations indicate that our proposed method efficiently allocates routes with smaller taxiing time, as well as fewer aircraft stops during the taxiing process

Preference-based evolutionary algorithm for airport surface operations

In addition to time efficiency, minimisation of fuel consumption and related emissions has started to be considered by research on optimisation of airport surface operations as more airports face severe congestion and tightening environmental regulations. Objectives are related to economic cost which can be used as preferences to search for a region of cost efficient and Pareto optimal solutions. A multi-objective evolutionary optimisation framework with preferences is proposed in this paper to solve a complex optimisation problem integrating runway scheduling and airport ground movement problem. The evolutionary search algorithm uses modified crowding distance in the replacement procedure to take into account cost of delay and fuel price. Furthermore, uncertainty inherent in prices is reflected by expressing preferences as an interval. Preference information is used to control the extent of region of interest, which has a beneficial effect on algorithm performance. As a result, the search algorithm can achieve faster convergence and potentially better solutions. A filtering procedure is further proposed to select an evenly distributed subset of Pareto optimal solutions in order to reduce its size and help the decision maker. The computational results with data from major international hub airports show the efficiency of the proposed approach