Scheduling Aircraft Landings Under Constrained Position Shifting

Abstract

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 amang aircraft that arise either from a i r h e 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

A Study of Tradeoffs in Scheduling Terminal-Area Operations

“…In prior work, it has been shown that every feasible k-CPS sequence can be represented as a path in a directed graph whose size is polynomially bounded in n and k [16]. This enables us to solve the problem at hand using dynamic programming, as is demonstrated in this section.…”

“…The maximum number of position shifts allowed is denoted by k (k 3 for most runway systems), and the resulting environment is referred to as a k-CPS scenario. The restricted deviation from the FCFS order helps maintain equity among aircraft operators and also increases the predictability of landing times [16].…”

“…An important objective, maximizing runway throughput (or, alternatively, minimizing the completion time of a sequence of aircraft), was considered in prior work, and a dynamic programming based solution approach was proposed [16]. Minimizing the average delay or minimizing a weighted sum of delays, where the weights represent the relative priorities of flights (based on factors such as crew schedules, passenger and fleet connectivity, turnaround times, gate availability, on-time performance, fuel status, and runway assignments), are also desirable objectives [19].…”

“…Several researchers in both the United States and Europe have since used CPS to model fairness and worked toward developing fast solution techniques for scheduling within the CPS framework [1], [7], [13]. While some variants of CPS were shown to be solvable in polynomial time [14], [15], they were unable to handle all the operational constraints that arose in practice [16]. More importantly, these methods lack a unifying theory that allows their results to generalize to other interesting scheduling problems under CPS, even resulting in a conjecture that, in general, scheduling under CPS may have exponential complexity [7].…”

“…In prior research, the scheduling problem of maximizing runway throughput under CPS was investigated [16]. A sequencing algorithm to take account of airline priorities was introduced [19].…”