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Metaheuristic algorithms for the simultaneous slot allocation problem

Metaheuristic algorithms for the simultaneous slot allocation problem

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© The Institution of Engineering and Technology
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In this study, the authors propose the formalisation of the Simultaneous Slot Allocation Problem (SSAP), that extends, in two directions, the current way of allocating airport slots in Europe. The SSAP requires, first, to perform the slot allocation at all airports simultaneously and, second, to respect airspace sector capacities. The authors solve the SSAP with two algorithms based on metaheuristics, namely Iterated Local Search and Variable Neighborhood Search, and with an algorithm based on an integer linear programming model. They compare these algorithms on randomly generated instances and show that for small instances metaheuristics are competitive with the integer linear programming model. Nevertheless, the integer linear programming model is unable to solve medium or large instances because of memory and computation time requirements. Metaheuristics, instead, can deal with large instances, allocating slots to more than 99.8% of flights.

Inspec keywords: integer programming; search problems; iterative methods; airports; resource allocation; linear programming

Other keywords: memory requirement; randomly generated instance; variable neighborhood search algorithm; integer linear programming model; iterated local search algorithm; medium instance; large instance; computation time requirement; airspace sector capacity; Europe; simultaneous slot allocation problem; airport slot allocation; metaheuristic algorithm; small instance; SSAP

Subjects: Systems theory applications in transportation; Interpolation and function approximation (numerical analysis); Combinatorial mathematics; Optimisation techniques

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