Hybrid method for aircraft landing scheduling based on a Job Shop formulation

This paper aims to study the multiple runway case of the static Aircraft Landing Problem (ALP), where all data are known in advance. In the first part of this work, we propose a formulation of the problem as a mathematical programming model in order to reduce the number of constraints (which can positively reduce the computing time) and to give a more rigorous formulation. In the second part, we formulate the ALP as a Job Shop Scheduling Problem (JSSP) based on a graphical representation. The interest of this second formulation is to show the relation between the ALP as a specific scheduling problem and the NP-hard JSSP as a more general Scheduling. Finally, to resolve the ALP, we propose a hybrid method combining Genetic Algorithms with Ant Colony Optimization Algorithm. The hybrid algorithm is tested on variant instances of the ALP, involving up to 50 aircraft and 4 runways.