A two-level optimization approach for robust aircraft routing and retiming

Abstract We investigate the Robust Aircraft Routing and Retiming Problem that is defined as follows. Given a set of flight legs to be served by a set of aircraft fleets, together with a tentative schedule, the problem requires determining a route assignment for each aircraft and the departure time of each flight leg so as to cover each flight by exactly one aircraft while satisfying operational constraints. The objective is to derive robust solutions that are less vulnerable to unpredictable disruptions caused by late-arriving aircraft. Ultimately, the goal being to enhance the airline on-time performance which is considered as a key performance measure since it greatly impinge on the airline profitability. In this paper, robustness is achieved through inserting time buffers in front of selected flight departure times. Toward this end, we propose a novel two-level solution strategy that embeds a simulation-optimization procedure within an evolutionary algorithm. At the first level, two mixed-integer quadratic programming models are iteratively solved for generating feasible trial solutions whose robustness is assessed by invoking a simulation procedure together with a Particle Swarm Optimization (PSO) procedure for guiding the search process. At the second level, an evolutionary algorithm is used for iteratively improving the solution that is generated at the first level. We present the results of extensive computational experiments that were carried out on a set of real data, with up to 1278 flights, and that demonstrate the benefits of the two-level approach.