Simulation optimization of airline delay using simultaneous perturbation stochastic approximation

Abstract

Air traffic delay is a growing and expensive problem. We looked at ways to reduce the cost and magnitude of such delays by trading gate delays against more expensive air delays. 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. Since the model is stochastic, these measures are noisy. The objective was to determine a set of control measures that achieve the best system performance subject to restrictions on the decision parameters and selected outputs of the model. This is a constrained stochastic optimization problem with nonlinear objective function 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.