Particle swarm optimization for airlines fleet assignment

Abstract

Airline fleet assignment is the process of assigning aircraft types to scheduled flight legs in order to minimize operating cost and achieve maximize revenue, while satisfying a set of constraints. This paper formulate the fleet assignment problem for airlines that optimization goal is to minimize the total assignment cost. Particle swarm optimization proposed to solve this model. The model successfully applied to Egyptair airline dataset using the particle swarm optimization and mixed integer programming. The proposed method compared with mixed integer programming and current Egyptair assignment methodology. The results showed that the particle swarm optimization is the best method for the Egyptair fleet assignment process. The solution quality is better than mixed integer programming and Egyptair assignment methodology where we saw a daily cost reduction with a percentage of 14.6% and 19.3% respectively.