Empirical model-building and response surface
Empirical model-building and response surface
An experimental procedure for simulation response surface model identification
Communications of the ACM
Design of frequency-domain experiments for discrete-valued factors
Applied Mathematics and Computation
Driving frequency selection for frequency domain simulation experiments
Operations Research
Taguchi's parameter design: a panel discussion
Technometrics
Using central composite designs in simulation experiments
WSC '92 Proceedings of the 24th conference on Winter simulation
Variance reallocation in Taguchi's robust design framework
WSC '92 Proceedings of the 24th conference on Winter simulation
WSC '94 Proceedings of the 26th conference on Winter simulation
Experimental designs for system assessment and improvement when noise factors are correlated
WSC '94 Proceedings of the 26th conference on Winter simulation
Response surface methodology and its application in simulation
WSC '93 Proceedings of the 25th conference on Winter simulation
Sensitivity and scenario analysis for simulation metamodels
WSC '96 Proceedings of the 28th conference on Winter simulation
Designing simulation experiments: Taguchi methods and response surface metamodels
WSC '91 Proceedings of the 23rd conference on Winter simulation
Solution to the indexing problem of frequency domain simulation experiments
WSC '91 Proceedings of the 23rd conference on Winter simulation
A model for frequency domain experiments
WSC '87 Proceedings of the 19th conference on Winter simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Output modeling: abc's of output analysis
Proceedings of the 33nd conference on Winter simulation
Design of experiments: designing simulation experiments
Proceedings of the 33nd conference on Winter simulation
Simulation experiments: designing simulation experiments
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
General methodology 1: a robust simulation-based multicriteria optimization methodology
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Issues on simulation and optimization I: robust simulation-based design of hierarchical systems
Proceedings of the 35th conference on Winter simulation: driving innovation
Issues on simulation and optimization II: robust hybrid designs for real-time simulation trials
Proceedings of the 35th conference on Winter simulation: driving innovation
Designing simulation experiments
WSC '04 Proceedings of the 36th conference on Winter simulation
Work smarter, not harder: guidelines for designing simulation experiments
WSC '05 Proceedings of the 37th conference on Winter simulation
Work smarter, not harder: guidelines for designing simulation experiments
Proceedings of the 38th conference on Winter simulation
State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments
INFORMS Journal on Computing
Work smarter, not harder: guidelines for designing simulation experiments
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
A web-based simulation optimization system for industrial scheduling
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Better than a petaflop: the power of efficient experimental design
Proceedings of the 40th Conference on Winter Simulation
Simulation optimization for industrial scheduling using hybrid genetic representation
Proceedings of the 40th Conference on Winter Simulation
Designing simulation experiments with controllable and uncontrollable factors
Proceedings of the 40th Conference on Winter Simulation
Better than a petaflop: the power of efficient experimental design
Winter Simulation Conference
Application of central composite design to simulation experiment
AsiaSim'04 Proceedings of the Third Asian simulation conference on Systems Modeling and Simulation: theory and applications
Work smarter, not harder: a tutorial on designing and conducting simulation experiments
Proceedings of the Winter Simulation Conference
Better than a petaflop: the power of efficient experimental design
Proceedings of the Winter Simulation Conference
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We describe a framework for analyzing simulation output in order to find solutions that will work well after implementation. We show how the use of a loss function that incorporates both system mean and system variability can be used to efficiently and effectively carry out system optimization and improvement efforts. For models whose behavior depends on quantitative factors, we illustrate how robust design can be accomplished by using simple experimental designs in conjunction with response-surface metamodels. The results can yield new insights into system behavior, and may lead to recommended system configurations that differ substantially from those selected by analysis solely on the basis of mean response. We assume a knowledge base at the level of Chapter 12 of Simulation Modeling and Analysis (Law and Kelton 2000) but will review essential elements and distribute illustrative examples at the session.