Article ID: | iaor20084108 |
Country: | Netherlands |
Volume: | 173 |
Issue: | 1 |
Start Page Number: | 30 |
End Page Number: | 46 |
Publication Date: | Aug 2006 |
Journal: | European Journal of Operational Research |
Authors: | Kao Chiang, Chen Shih-Pin |
Keywords: | simulation: applications |
Simulation response optimization has wide applications for management of systems that are so complicated that the performance can only be evaluated by using simulation. This paper modifies the quasi-Newton method used in deterministic optimization to suit the stochastic environment in simulation response optimization. The basic idea is to use the estimated subgradient calculated from different replications and a metric matrix updated from the Broyden–Fletcher–Goldfarb–Shanno formula to yield a quasi-Newton search direction. To avoid misjudging the minimal point, in both the line search and the quasi-Newton iterations, due to the stochastic nature, a