Proceedings of the 33nd conference on Winter simulation
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
Experimental design for simulation: experimental design for simulation
Proceedings of the 35th conference on Winter simulation: driving innovation
Simulation for the Social Scientist
Simulation for the Social Scientist
Designing simulation experiments
WSC '04 Proceedings of the 36th conference on Winter simulation
Design and Analysis of Experiments
Design and Analysis of Experiments
Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
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
Design and Analysis of Simulation Experiments
Design and Analysis of Simulation Experiments
Efficient experimental design tools for exploring large simulation models
Computational & Mathematical Organization Theory
A Plea for (Good) Simulations: Nudging Economics Toward an Experimental Science
Simulation and Gaming
Epistemological perspectives on simulation: overview and introduction
Computational & Mathematical Organization Theory
Computational & Mathematical Organization Theory
Metamodels for role-driven agent-based modelling
Computational & Mathematical Organization Theory
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Many still view simulation models as a black box. This paper argues that perceptions could change if the systematic design of experiments (DOE) for simulation research was fully realized. DOE can increase (1) the transparency of simulation model behavior and (2) the effectiveness of reporting simulation results. Based on DOE principles, we develop a systematic procedure to guide the analysis of simulation models as well as concrete templates for sharing the results. A simulation model investigating the performance of learning algorithms in an economic mechanism design context illustrates our suggestions. Overall, the proposed systematic procedure for applying DOE principles complements current initiatives for a more standardized simulation research process.