The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Simulation modeling with event graphs
Communications of the ACM
The time and state relationships in simulation modeling
Communications of the ACM - Special issue on simulation modeling and statistical computing
An introduction to general systems thinking (silver anniversary ed.)
An introduction to general systems thinking (silver anniversary ed.)
Control Systems Engineering
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Theory of Computation
Verification and validation: verification and validation of simulation models
Proceedings of the 35th conference on Winter simulation: driving innovation
When and how to develop domain-specific languages
ACM Computing Surveys (CSUR)
As simple as possible, but no simpler: a gentle introduction to simulation modeling
Proceedings of the 38th conference on Winter simulation
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
Development of a container terminal educational simulator
ACS'08 Proceedings of the 8th conference on Applied computer scince
Understanding design activities through computer simulation
Advanced Engineering Informatics
Business process adaptation on a tracked simulation model
Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research
Business process performance prediction on a tracked simulation model
Proceedings of the 3rd International Workshop on Principles of Engineering Service-Oriented Systems
Defining background tasks in SimFC
Proceedings of the Winter Simulation Conference
Model development in discrete-event simulation: insights from six expert modelers
Proceedings of the Winter Simulation Conference
Programming and Computing Software
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We start with basic terminology and concepts of modeling, and decompose the art of modeling as a process. This overview of the process helps clarify when we should or should not use simulation models. We discuss some common missteps made by many inexperienced modelers, and propose a concrete approach for avoiding those mistakes. After a quick review random number and random variate generation, we view the simulation model as a black-box which transforms inputs to outputs. This helps frame the need for designed experiments to help us gain better understanding of the system being modeled.