Elements of simulation
Stochastic simulation
Statistical tools for simulation practitioners
Statistical tools for simulation practitioners
A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Simulation methodology for statisticians, operations analysts, and engineers: vol. 1
Simulation methodology for statisticians, operations analysts, and engineers: vol. 1
WSC '92 Proceedings of the 24th conference on Winter simulation
Designing efficient simulation experiments
WSC '92 Proceedings of the 24th conference on Winter simulation
Factor screening of multiple responses
WSC '92 Proceedings of the 24th conference on Winter simulation
Advanced output analysis for simulation
WSC '92 Proceedings of the 24th conference on Winter simulation
A tutorial on simulation optimization
WSC '92 Proceedings of the 24th conference on Winter simulation
Perturbation analysis: concepts and algorithms
WSC '92 Proceedings of the 24th conference on Winter simulation
Experimental design issues in simulation with examples from semiconductor manufacturing
WSC '92 Proceedings of the 24th conference on Winter simulation
Gradient estimation for regenerative processes
WSC '92 Proceedings of the 24th conference on Winter simulation
Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
Graphical techniques for output analysis
WSC '92 Proceedings of the 24th conference on Winter simulation
WSC '94 Proceedings of the 26th conference on Winter simulation
Designing simulation experiments for evaluating manufacturing systems
WSC '94 Proceedings of the 26th conference on Winter simulation
WSC '94 Proceedings of the 26th conference on Winter simulation
Efficiency improvement and variance reduction
WSC '94 Proceedings of the 26th conference on Winter simulation
A review of advanced methods for simulation output analysis
WSC '94 Proceedings of the 26th conference on Winter simulation
A tutorial review of techniques for simulation optimization
WSC '94 Proceedings of the 26th conference on Winter simulation
Ranking, selection and multiple comparisons in computer simulations
WSC '94 Proceedings of the 26th conference on Winter simulation
A tutorial on design and analysis of simulation experiments
WSC '95 Proceedings of the 27th conference on Winter simulation
Statistical analysis of output processes
WSC '93 Proceedings of the 25th conference on Winter simulation
Advanced simulation output analysis for a single system
WSC '93 Proceedings of the 25th conference on Winter simulation
Gradient/sensitivity estimation in discrete-event simulation
WSC '93 Proceedings of the 25th conference on Winter simulation
Response surface methodology and its application in simulation
WSC '93 Proceedings of the 25th conference on Winter simulation
Output analysis for simulation
WSC '91 Proceedings of the 23rd conference on Winter simulation
Designing simulation experiments: Taguchi methods and response surface metamodels
WSC '91 Proceedings of the 23rd conference on Winter simulation
Methods for selecting the best system
WSC '91 Proceedings of the 23rd conference on Winter simulation
Multivariate simulation output analysis
WSC '91 Proceedings of the 23rd conference on Winter simulation
An overview of derivative estimation
WSC '91 Proceedings of the 23rd conference on Winter simulation
Principles of Discrete Event Simulation
Principles of Discrete Event Simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Simulation for Decision Making
Simulation for Decision Making
Statistical analysis of simulation output
Proceedings of the 29th conference on Winter simulation
Application of simulation to scheduling, sequencing, and material handling
Proceedings of the 29th conference on Winter simulation
Introduction to the art and science of simulation
Proceedings of the 30th conference on Winter simulation
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This paper describes, in general terms, methods to help design the runs for simulation models and in terpreting their output. Statistical methods are described for several different purposes, and related problems like comparison, variance reduction, sensitivity estimation, metamodeling, and optimization are mentioned. The main point is to call attention to the challenges and opportunities in using simulation models carefully and effectively.