Multiobjective optimization for aircraft conflict resolution. A metaheuristic approach - Alonso-Ayuso, Antonio; Escudero, Laureano F.; Martín-Campo, F. Javier (European journal of operational research, 2016)
•A scheme for the Conflict Resolution problem in Air Traffic Management is presented.•A mixed integer nonlinear optimization model is considered.•A Sequential approach for Goal Programming is proposed.•An extensive computational experience with more than 200 instances is reported.•Computational comparison between the MINO solver Minotaur and the proposed approach. The conflict resolution problem in Air Traffic Management is tackled in this paper by using a mixed integer linear approximation to a Mixed Integer Nonlinear Optimization (MINO) model that we have presented elsewhere. The aim of the problem consists of providing a new aircraft configuration such that every conflict situation is avoided, a conflict being an event in which two or more aircraft violate the minimum safety distance that they must keep in flight. The initial information consists of the aircraft configuration in a certain time instant: position, velocity, heading angle and flight level. The proposed approach allows the aircraft to perform any of the three possible maneuvers: velocity, turn angle and flight level changes. The nonlinear model involves trigonometric functions which make it difficult to solve, in addition to the integer variables related to flight level changes, among other auxiliary variables. A multicriteria scheme based on Goal Programming is also presented. In order to provide a good solution in short computing time, a Sequential Mixed Integer Linear Optimization (SMILO) approach is proposed. A comparison between the results obtained by using the state-of-the-art MINO solver Minotaur and SMILO is performed to assess the solution’s quality. Based on the computational results that we have obtained in a broad testbed we have experimented with, SMILO provides a very close solution to the one provided by Minotaur practically for all the instances. SMILO requires a very small computing time that makes the approach very suitable for helping to solve real-life operational situations.