Abstract:
We introduce Direct Gradient Augmented Response Surface Methodology (DiGARSM), a new sequential first-order method for optimizing a stochastic function based on Response ...Show MoreMetadata
Abstract:
We introduce Direct Gradient Augmented Response Surface Methodology (DiGARSM), a new sequential first-order method for optimizing a stochastic function based on Response Surface Methodology (RSM). In this approach, gradients of the objective function with respect to the desired parameters are utilized in addition to response measurements. We establish convergence of the proposed method. We compare methods that use only response information and those that use only gradient information with the proposed approach, which uses both. Moreover, we conduct numerical simulations to illustrate the effectiveness of the proposed method.
Published in: 2018 Winter Simulation Conference (WSC)
Date of Conference: 09-12 December 2018
Date Added to IEEE Xplore: 03 February 2019
ISBN Information: