Introduction to operations research, 4th ed.
Introduction to operations research, 4th ed.
Response surface methodology: 1966–1988
Technometrics
Taguchi's parameter design: a panel discussion
Technometrics
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments
INFORMS Journal on Computing
Designing simulation experiments with controllable and uncontrollable factors
Proceedings of the 40th Conference on Winter Simulation
Kriging metamodel management in the design optimization of a CNG injection system
Mathematics and Computers in Simulation
Design and Analysis of Simulation Experiments
Design and Analysis of Simulation Experiments
Metamodel variability analysis combining bootstrapping and validation techniques
Proceedings of the Winter Simulation Conference
A multicriteria simulation optimization method for injection molding
Proceedings of the Winter Simulation Conference
Proceedings of the Winter Simulation Conference
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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.