Steady State Evolutionary Algorithm and Operators for the Airport Gate Assignment Problem

Abstract

Correct assignment of airport resources can greatly affect the quality of service which airlines and airports provide to their customers. Good assignments can help airlines and airports keep to published schedules, by minimising changes in published schedules, reducing delays, and considering the different stakeholder interests. When taking into account the passenger's walking distance, the Airport Gate Assignment Problem (AGAP) can be modeled by analogy with the NP-hard quadratic assignment problem. Also given the expected increases in civil air traffic, the complexities of the resource assignment problems continue to increase. For these reasons, as well as the dynamic nature of the problems, scheduling has become more difficult. The Steady State Evolutionary Algorithm (SSEA) used in the Airport Baggage Sorting Station Assignment Problem (ABSSAP) is potentially important for a wider variety of problems other than the ABSSAP. By way of illustration, here we look at applying the SSEA to the more widely studied AGAP. Some of the metaheuristics and constructive algorithms previously used in the ABSSAP are modified, modifications which are required to be able to apply these metaheuristics to the AGAP, and the constructive algorithms are used as initial solutions in the SSEA presented here for the AGAP. The SSEA is studied, and compared with other metaheuristics approaches, which performance is studied in regard to the different objectives used at London Heathrow airport.