Simulation optimization of airline delay with constraints and multiple objectives

Air traffic delay is a growing and expensive problem. We investigated ways to reduce the cost and magnitude of such delays by means of several control strategies. Air management and planning at this level can be facilitated by simulation, especially for strategies that alter controls on the system. We used the SIMMOD air traffic simulation to model the system. The goal was to determine a set of control measures that achieve the best system performance subject to restrictions on the decision parameters and selected output measurements. Because observed system performance is "noisy," the problem is a constrained stochastic optimization problem with multiple nonlinear objective functions and nonlinear, stochastic constraints, which requires efficient stochastic optimization methods for its solution. Our approach used simultaneous perturbation stochastic approximation (SPSA) with a penalty function to handle the difficult constraints. The results are illustrated in simulation experiments

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