| Constraint programming offers a variety of modeling techniques that ease the challenging notion of solving combinatorial optimization problems. By adding problem-dependent constraints without having to modify the solution strategy, constraint programming provides several advantages over the traditional mathematical programming techniques. We uncover the underlying mechanism of constraint programming and extend our studies to scheduling problems such as the single-airport Ground Holding and Free Flight problems, and the railway locomotive scheduling problem. Optimization techniques to solve Ground Holding and Free Flight problems play an eminent role in the airline industry. Comparison studies between the traditional mathematical programming models and the proposed constraint programming models are provided.; Furthermore, a different type of novel optimization technique is discussed, specifically simulation and optimization. Using simulation, the problem of Taxi Brake Select® is analyzed and a special type of artificial intelligence, namely reinforcement learning, is adapted in order to improve the cost and safety of the aircraft and to make the taxi brake system flexible to integrate different types of aircrafts. |
