INTELLIGENT SIMULATION FOR ALTERNATIVES COMPARISON AND APPLICATION TO AIR TRAFFIC MANAGEMENT

1.Introduction Computer simulation technology has matured over the past decade and is now commonly used to evaluate large-scale real systems with complex stochastic behavior.Simulation allows one to more accurately specify a system through the use of logically complex,and often non-algebraic,variables and constraints.This capability compliments the inherent limitation of traditional optimization.However,the added flexibility often creates models that are computationally intractable.The effici…

Intelligent simulation for alternatives comparison and application to air traffic management

We present a simulation run allocation scheme for improving efficiency in simulation experiments for decision making under uncertainty. This scheme is called Optimal Computing Budget Allocation (OCBA). OCBA advances the state-of-the-art by intelligently allocating a computing budget to the candidate alternatives under evaluation. The basic idea is to spend less computational effort on simulating non-critical alternatives to save computation cost. In particular, OCBA is employed to intelligently provide the smallest number of simulation runs for a desired accuracy. In this paper, we present a new and more general OCBA scheme which can consider cases that users are interested not only the best design, but also any one in a good design set. In addition, this paper also presents the application of our OCBA to a design problem in US air traffic management. The national air traffic system in US is modeled as a large, complex, and stochastic network. The numerical examples show that the computation time can be reduced by 54% to 88% with the use of OCBA.