Multiairport Ground Holding Problem: A Computational Evaluation of Exact Algorithms

Abstract

Congestion in the air traffic network is becoming an increasingly serious problem that causes inconvenience to passengers, losses to airlines and, last but not least, threats to airspace safety. One way of reducing the amount of congestion is to use Ground Holding policies, i.e., to impose on selected aircraft a ground holding prior to their departure so that congestion during peak periods of time may be smoothed away. In this paper we restrict our attention to the Multiairport Ground Holding problem, where congestion may arise only at the airports due to limited arrival capacity. There are a few algorithms that, under suitable hypotheses, find an “optimal” policy for the Multiairport Ground Holding problem. In this paper we evaluate and compare computationally three of them, namely, the one recently proposed by Vranas, Bertsimas and Odoni, the one suggested by Andreatta and Tidona and that due to Bertsimas and Stock. The computational evaluation is based on two sets of test problems. The first set consists of seven problems taken from the literature. The second set consists of 32 “realistic” test problems. The results indicate the superiority of the Bertsimas and Stock approach among the three models considered.

Multiairport Capacity Management: Genetic Algorithm With Receding Horizon

“…The crossover and mutation probabilities are calculated in (12) and (13), shown at the bottom of the page, where P c and P m are, respectively, the crossover and mutation probabilities for evolving a certain chromosome in a certain generation, f max is the maximum fitness in the generation, and f avg is the average fitness of the generation. When the generation converges to a local optimum (f max − f avg is very small), according to (13), P m will increase to diversify the following generation. In the reverse case (f max − f avg is very large), P c will increase to speed up convergence.…”

“…Recently, research attention has been moving to air traffic management in multiairport systems. Models and algorithms developed based on single airport systems have been extended to more complicated multiairport cases [11]- [13]. For example, the cutting plane algorithm and integer programming were applied to multi-ACM based on an open network model in [11]; dynamic programming and network topology were used for multiairport traffic flow coordination in [12]; and methods to attack the multiairport ground holding problem were particularly studied in [13].…”

Study of the Multi-Airport Ground-holding Strategy Model and Application

“…Odoni [2] study the single airport in detail. Brunetta et al [3][4][5][6][7] propose flight priority rules, considering the different delay costs of flight and propose a cost function based on flight priority. Ravizza et al [8] analyze the data of European hub airport, and put forward the sequence diagram algorithm to reduce delay cost, fuel cost and pollution cost.…”

The Traffic Flow Management Rerouting Problem in Air Traffic Control: A Dynamic Network Flow Approach

“…Earlier work has focused on (a) controlling release times of aircraft in the network (ground- holding) in a single airport setting (TERRAB and ODONI, 1991;ODONI, 1993, 1994), and in a multiple airport setting, in which delays propagate through the network (TERRAB and PAULOSE, 1993, VRANAS, BERTSIMAS, and ODONI 1994a, b, AN-DREATTA and TIDONA, 1994, BERTSIMAS and STOCK PATTERSON, 1998, ANDREATTA and BRUNETTA, 1998, BRUNETTA, GUASTALLA, and NAVAZIO 1996 controlling release times and speed adjustments of aircraft while airborne for a network of airports taking into account the capacitated airspace (Bertsimas and Stock Patterson, 1998;HELME, 1994;LINDSAY, BOYD, and BURLINGAME, 1993). For a discussion of the various contributions and a taxonomy of the various problems, see Bertsimas and Stock Patterson (1998) and Andreatta and Brunetta (1998).…”