Abstract
In the past decades, the increase of civil air-traffic and the corresponding growth of airports have highlighted the importance of the gate scheduling as a key activity in airport operations. To solve this problem, different mathematical models for flights assignment to gates can often be found in technical literature. In this work we propose a method based on the Bee Colony Optimization (BCO) to find an optimal flight gate assignment for a given schedule. This metaheuristic represents an interesting methodology in the field of Swarm Intelligence for its capability to solve high level combinatorial problems with fast convergence performances. The proposed methodology includes a multicriteria analysis considering two main objectives: minimization of passenger total walking distance and remote gate usage. Results of the comparison with the Milano-Malpensa airport schedule highlight the effectiveness of the proposed method.
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