Robert G. Sargent

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In this paper we discuss validation and verfication of simulation models. Four different approaches to deciding model validity are described; two different paradigms that relate validation and verification to the model development process are presented; various validation techniques are defined; conceptual model validity, model verification, operational(More)
This expository paper discusses the relationships among metamodels, simulation models, and problem entities. A metamodel or response surface is an approximation of the input/output function implied by the underlying simulation model. There are several types of metamodel: linear regression, splines, neural networks, etc. This paper distinguishes between(More)
New analytical and empirical results for the performance of future event set algorithms in discrete event simulation are presented. These results provide a clear insight to the factors affecting algorithm performance, permit evaluation of the hold model, and determine the best algorithm(s) to use. The analytical results include a classification of(More)
This is a tutorial paper on validation of simulation models. Included in this tutorial are what is meant by validation, the problem dependent characteristics of simulation model validation, descriptions of the various validation techniques and their use and a discussion on the statistics used in validation techniques (but not the detailed statistical tests(More)
This paper discusses verification and validation of simulation models. The different approaches to deciding model validity am presented; how model verification and validation relate to the model development process are discussed; various validation techniques are defined, conceptual model validity, model verification, operational validity, and data validity(More)
A methodology is presented for constructing the relationships among model user's risk, model builder's risk, acceptable validity range, sample sizes, and cost of data collection when statistical hypothesis testing is used for validating a simulation model of a real, observable system. The use of the methodology is illustrated for the use of Hotelling's(More)
In this paper we discuss verification and validation of simulation models. The different approaches to deciding model validity are described, two different paradigms that relate verification and validation to the model development process are presented, the use of graphical data statistical references for operational validity is discussed, and a recommended(More)
This paper discusses verification and validation of simulation models. The different approaches to deciding model validity are described; how model verification and validation relate to the model development process is specified; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity(More)