Combinatorial Search Space Reduction Approach In Aircraft Schedule Recovery Problem

The curse of dimensionality often poses challenges for combinatorial optimization techniques. Therefore, it is crucial to employ an effective technique that can efficiently reduce the search space and enhance the performance of the optimization algorithm. This study proposes a modified selection heuristic approach for subnetwork selection in the aircraft schedule recovery problem. This algorithm optimizes the allocation of flights to the selected aircraft subset. To evaluate its effectiveness, we compare it with the optimization of the entire network of a major airline company. The performance of the selection heuristic is tested on 39 aircraft, 147 flights, and 42 airports. The results demonstrate a significant improvement in the overall runtime of the optimization algorithm while giving the optimal solutions in most cases.