Abstract:
Optimization of simulated systems is the goal of many methods, but most methods assume known environments. In this paper we present a methodology that does account for un...View moreMetadata
Abstract:
Optimization of simulated systems is the goal of many methods, but most methods assume known environments. In this paper we present a methodology that does account for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by either Response Surface Methodology or Kriging metamodeling. We illustrate the resulting methodology through the well-known Economic Order Quantity (EOQ) model.
Date of Conference: 13-16 December 2009
Date Added to IEEE Xplore: 11 March 2010
ISBN Information: