A new perspective of the validation problemfor simulation models is formulated in this article. The approach is knowledge-based and focuses on behavioral validation. It has the important feature of providing a basis for the development of a software environment that can automate the validation activity. Discrete, continuous and combined simulation models can be treated in a uniform manner. The key element of the approach is a validation knowledge base (VKB). This is developed as three disjoint sets of relationships among the input and output variables of the simulation model. These relationships serve to capture all aspects of expected behavior of the simulation model. A simple characterization of model behavior is presented which provides the basis for specifying the relationships from which the VKB is constructed The utilization of all the information in the VKB in an efficient way is an important subgoal of our system architecture. This requirement gives rise to an experiment design problem. This problem is carefully formulated and examined within the framework of the behavior characterizations that exist in the VKB. In particular, a basis for its solution is established in a constraint set framework by carrying out a transformation on the relationships within the VKB. The constraint set context for the problem has the advantage of providing an environment which not only facilitates analysis but also enables the application of a variety of solution techniques.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.
The use of models as a means of obtaining insight or understanding is by no means novel. One could reasonably claim, for example, that the pivotal studies in geometry carried out by Euclid were motivated by the desire to construct models that would assist in better understanding important aspects of his physical environment. It could also be observed that it is rare indeed for the construction of even the most modest of structures to be undertaken without some documented perspective (i.e. an architectural plan or drawing) of the intended form. Such a document represents a legitimate model for the structure and serves the important purpose of providing guidance for its construction. Many definitions of a model can be found in the literature. One that we feel is especially noteworthy was suggested by Shannon [19]: 'A model is a representation of an object, system or idea in some form other than itself'.Although outside the scope of our considerations, it is important to recognize a particular and distinctive class of models called physical models. These provide the basis for experimentation activity within an environment that mimics the physical environment in which the problem originates. An example here is the use of scale models of aircraft or ships within a wind tunnel to evaluate aerodynamic properties; another is the use of 'crash-test dummies' in the evaluation of automobile safety characteristics. A noteworthy feature of physical models is that they can, at least in principle, provide the means for direct acquisition of relevant experimental data. However, the necessary instrumentation may be exceedingly difficult to implement.A fundamental dichotomy among models can be formulated on the basis of the role of time; more specifically, we note that some models are dynamic while others are static. A linear programming model for establishing the best operating point for some enterprise under a prescribed set of conditions is a static model because there is no notion of time dependence embedded in such a model formulation. Likewise, the use of tax software to establish the amount of income tax payable by an individual to the government can be regarded as the process of developing a (static)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.