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.
Robust simulation-optimization using metamodels / Dellino, G; Kleijnen, Jpc; Meloni, Carlo. - (2009), pp. 540-550. (Intervento presentato al convegno 2009 Winter Simulation Conference, WSC 2009 tenutosi a Austin, TX nel December 13-16, 2009) [10.1109/WSC.2009.5429720].
Robust simulation-optimization using metamodels
MELONI, Carlo
2009-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
