A Multi-Objective Evolutionary Algorithm for the Problem of Scheduling Single-Runway Aircraft Landings

In this study, a metaheuristic algorithm based on an evolutionary approach with multiple objectives of minimizing the total cost of divergence and makespan, denominated Multi-objective Particle Swarm Optimization (MOPSO), is proposed to solve the Aircraft Landing Problem involving single-runway configurations. The performance of the algorithm is evaluated through a set of instances found in the literature, involving up to 20 aircraft. The computational results show that the proposed heuristic proved to be relevant in the generation of good quality solutions, in a considerable computational time, given the number of aircraft and particular characteristics of each instance.