A conceptual solution to the aircraft gate assignment problem using 0,1 linear programming
Proceedings of the 12th annual conference on Computers and industrial engineering
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The Airport Gate Assignment Problem: Mathematical Model and a Tabu Search Algorithm
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 3 - Volume 3
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
The over-constrained airport gate assignment problem
Computers and Operations Research
Genetic algorithm based on receding horizon control for arrival sequencing and scheduling
Engineering Applications of Artificial Intelligence
Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms
IEEE Transactions on Evolutionary Computation
A ripple-spreading genetic algorithm for the aircraft sequencing problem
Evolutionary Computation
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Since the Gate Assignment Problem (GAP) at airport terminals is a combinatorial optimization problem, permutation representations based on aircraft dwelling orders are typically used in the implementation of Genetic Algorithms (GAs), The design of such GAs is often confronted with feasibility and memory-efficiency problems. This paper proposes a hybrid GA, which transforms the original order based GAP solutions into value based ones, so that the basic a binary representation and all classic evolutionary operations can be applied free of the above problems. In the hybrid GA scheme, aircraft queues to gates are projected as points into a parameterized space. A deterministic model inspired by the phenomenon of natural ripple-spreading on liquid surfaces is developed which uses relative spatial parameters as input to connect all aircraft points to construct aircraft queues to gates, and then a traditional binary GA compatible to all classic evolutionary operators is used to evolve these spatial parameters in order to find an optimal or near-optimal solution. The effectiveness of the new hybrid GA based on the ripple-spreading model for the GAP problem are illustrated by experiments.