Optimization of simulation via quasi-Newton methods

This paper discusses the application of quasi-Newton methods to optimization of simulation. Specifically, it describes a general methodology that combines response surface methodology and other optimization techniques with quasi-Newton methods. Using quasi-Newton methods in the vicinity of the optimum speeds up the convergence rate of response surface methodology, the gradient, and search methods. From the class of quasi-Newton methods, we recommend Broyden–Fletcher–Granno–Schmidt and Davidon's methods. These methods are effective without exact line searches. Two examples demonstrate the effectiveness of the proposed methodology.