Improved rolling horizon approaches to the aircraft sequencing problem

In a scenario characterized by a continuous growth of air transportation demand, the runways of large airports serve hundreds of aircraft every day. Aircraft sequencing is a challenging problem that aims to increase runway capacity in order to reduce delays as well as the workload of air traffic controllers. In many cases, the air traffic controllers solve the problem by using the simple “First-Come-First-Serve” (FCFS) rule. In this paper we present a rolling horizon approach which partitions a sequence of aircraft into chunks and solves the Aircraft Sequencing Problem (ASP) individually for each of these chunks. Some rules for deciding how to partition a given aircraft sequence are proposed and their effects on solution quality investigated. Moreover, two Mixed Integer Linear Programming (MILP) models for the ASP are reviewed in order to formalize the problem, and a tabu search heuristic is proposed for finding solutions to the ASP in a short computation time. Finally, we develop an IRHA which, by using different chunking rules, is able to find solutions significantly improving on the FCFS rule for real world air traffic instances from Milano Linate Airport.