Simulation optimization of airline delay with constraints and multiple objectives

Abstract

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.

Investigation of the Impact of the Air Traffic Route Configurations on Sector Capacity

“…The major outputs are travel time, traffic flow, capacity, delays and fuel consumption [8,9]. SIMMOD is used for various problems such as congestion, delay and capacity analysis [10][11][12], analysis of different runway configurations [13], infrastructure changes such as runway, taxiway and gates [14], and fuel, emissions and their effects [15,16]. In this study, the effects of the route configurations such as intersecting routes and the intersection angle on the average delay time, the sector capacity and occupancy, are examined.…”