Dynamic scheduling of aircraft landings

This paper considers the scheduling of aircraft landings on a single runway. There are time window constraints for each aircraft’s landing time, and minimum separation times between consecutive landings, where the separation times depend on the weight classes of the two landing aircraft. A multi-objective formulation takes account of runway throughput, earliness and lateness, and the cost of fuel arising from aircraft manoeuvres and additional flight time incurred to achieve the landing schedule. The paper investigates both the static/off-line problem where details of the arriving flights are known in advance, and the dynamic/on-line problem where flight arrival information becomes available over time. Under dynamic scheduling, the algorithm makes periodic updates to the previous schedule to take into account the aircraft that are newly available. We investigate dynamic programing and local search implementations for the static and dynamic problem using random test data and real data from London Heathrow airport

Scheduling aircraft landings - the static case

This is the publisher version of the article, obtained from the link below.In this paper, we consider the problem of scheduling aircraft (plane) landings at an airport. This problem is one of deciding a landing time for each plane such that each plane lands within a predetermined time window and that separation criteria between the landing of a plane and the landing of all successive planes are respected. We present a mixed-integer zero–one formulation of the problem for the single runway case and extend it to the multiple runway case. We strengthen the linear programming relaxations of these formulations by introducing additional constraints. Throughout, we discuss how our formulations can be used to model a number of issues (choice of objective function, precedence restrictions, restricting the number of landings in a given time period, runway workload balancing) commonly encountered in practice. The problem is solved optimally using linear programming-based tree search. We also present an effective heuristic algorithm for the problem. Computational results for both the heuristic and the optimal algorithm are presented for a number of test problems involving up to 50 planes and four runways.J.E.Beasley. would like to acknowledge the financial support of the Commonwealth Scientific and Industrial Research Organization, Australia

An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

Decentralized aircraft landing scheduling at single runway non-controlled airports

The existing air transportation system is approaching a bottleneck because its dominant huband- spoke model results in a concentration of a large percentage of the air traffic at a few hub airports. Advanced technologies are greatly needed to enhance the transportation capabilities of the small airports in the U.S.A., and distribute the high volume of air traffic at the hub airports to those small airports, which are mostly non-controlled airports. Currently, two major focus areas of research are being pursued to achieve this objective. One focus concentrates on the development of tools to improve operations in the current Air Traffic Management system. A more long-term research effort focuses on the development of decentralized Air Traffic Management techniques. This dissertation takes the latter approach and seeks to analyze the degree of decentralization for scheduling aircraft landings in the dynamic operational environment at single runway noncontrolled airports. Moreover, it explores the feasibility and capability of scheduling aircraft landings within uninterrupted free-flight environment in which there is no existence of Air Traffic Control (ATC). First, it addresses the approach of developing static optimization algorithms for scheduling aircraft landings and, thus, analyzes the capability of automated aircraft landing scheduling at single runway non-controlled airports. Then, it provides detailed description of the implementation of a distributed Air Traffic Management (ATM) system that achieves decentralized aircraft landing scheduling with acceptable performance whereas a solution to the distributed coordination issues is presented. Finally real-time Monte Carlo flight simulations of multi-aircraft landing scenarios are conducted to evaluate the static and dynamic performance of the aircraft landing scheduling algorithms and operation concepts introduced. Results presented in the dissertation demonstrate that decentralized aircraft landing scheduling at single runway non-controlled airports can be achieved. It is shown from the flight simulations that reasonable performance of decentralized aircraft landing scheduling is achieved with successful integration of publisher/subscriber communication scheme and aircraft landing scheduling model. The extension from the non-controlled airport application to controlled airport case is expected with suitable amendment, where the reliance on centralized air traffic management can be reduced gradually in favor of a decentralized management to provide more airspace capacity, flight flexibility, and increase operation robustness

Scheduling Aircraft Landings under Constrained Position Shifting

Optimal scheduling of airport runway operations can play an important role in improving the safety and efficiency of the National Airspace System (NAS). Methods that compute the optimal landing sequence and landing times of aircraft must accommodate practical issues that affect the implementation of the schedule. One such practical consideration, known as Constrained Position Shifting (CPS), is the restriction that each aircraft must land within a pre-specified number of positions of its place in the First-Come-First-Served (FCFS) sequence. We consider the problem of scheduling landings of aircraft in a CPS environment in order to maximize runway throughput (minimize the completion time of the landing sequence), subject to operational constraints such as FAA-specified minimum inter-arrival spacing restrictions, precedence relationships among aircraft that arise either from airline preferences or air traffic control procedures that prevent overtaking, and time windows (representing possible control actions) during which each aircraft landing can occur. We present a Dynamic Programming-based approach that scales linearly in the number of aircraft, and describe our computational experience with a prototype implementation on realistic data for Denver International Airport

A dynamic programming approach for the aircraft landing problem with aircraft classes

The capacity of a runway system represents a bottleneck at many international airports. The current practice at airports is to land approaching aircraft on a first-come, first-served basis. An active rescheduling of aircraft landing times increases runway capacity or reduces delays. The problem of finding an optimal schedule for aircraft landings is referred to as the “aircraft landing problem”. The objective is to minimize the total delay of aircraft landings or the respective cost. The necessary separation time between two operations must be met. Due to the complexity of this scheduling problem, recent research has been focused on developing heuristic solution approaches. This article presents a new algorithm that is able to create optimal landing schedules on multiple independent runways. Our numerical experiments show that problems with up to 100 aircraft can be optimally solved within seconds instead of hours that are needed to solve these problems with standard optimization tools

Space shuttle flying qualities and criteria assessment

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft

On the statistical description of the inbound air traffic over Heathrow airport

We present a model to describe the inbound air traffic over a congested hub. We show that this model gives a very accurate description of the traffic by the comparison of our theoretical distribution of the queue with the actual distribution observed over Heathrow airport. We discuss also the robustness of our model

Real-time adaptive aircraft scheduling

One of the most important functions of any air traffic management system is the assignment of ground-holding times to flights, i.e., the determination of whether and by how much the take-off of a particular aircraft headed for a congested part of the air traffic control (ATC) system should be postponed in order to reduce the likelihood and extent of airborne delays. An analysis is presented for the fundamental case in which flights from many destinations must be scheduled for arrival at a single congested airport; the formulation is also useful in scheduling the landing of airborne flights within the extended terminal area. A set of approaches is described for addressing a deterministic and a probabilistic version of this problem. For the deterministic case, where airport capacities are known and fixed, several models were developed with associated low-order polynomial-time algorithms. For general delay cost functions, these algorithms find an optimal solution. Under a particular natural assumption regarding the delay cost function, an extremely fast (O(n ln n)) algorithm was developed. For the probabilistic case, using an estimated probability distribution of airport capacities, a model was developed with an associated low-order polynomial-time heuristic algorithm with useful properties

Endogenous Control of Service Rates in Stochastic and Dynamic Queuing Models of Airport Congestion

Airport congestion mitigation requires reliable delay estimates. This paper presents an integrated model of airport congestion that combines a tactical model of capacity utilization into a strategic queuing model. The model quantifies the relationships between flight schedules, airport capacity and flight delays, while accounting for the way arrival and departure service rates can be controlled over the day to maximize operating efficiency. We show that the model estimates well the average and variability of the delays observed at New York’s airports. Results suggest that delays can be extremely sensitive to even small changes in flight schedules or airport capacity