Showing papers by "Bernard P. Zeigler published in 1984"

System-Theoretic Representation of Simulation Models

Abstract: The representation of simulation models, especially those expressed in discrete event languages, by means of system-theoretic formalism is reviewed. The important concepts of decomposition, static and dynamic structure, and state variable selection are explained and their implications for the design of simulation software explored. The system-theoretic approach is compared with other approaches to model representation derived from general software development methodology. Both simulation software design and systems theory may benefit by the challenges each raises for the other.

Multifaceted modeling methodology: Grappling with the irreducible complexity of systems

Abstract: The multifaceted modeling methodology discussed in this article is an approach to simulation modeling that realizes that reality is complex, and that, although this complexity is not reducible, partial models can be constructed to aid decision making. This methodology recognizes the need to integrate partial knowledge and solutions obtained under the constraints imposed by disciplinary or problem-oriented perspectives. Various concepts that facilitate this integration are reviewed.

System Theoretic Foundations of Modelling and Simulation

Abstract: Considering a model to be a system specification, this chapter reviews the hierarchy of levels at which a system can be specified and the formalisms in which the specification can be done. Such an approach provides a unification of modelling and simulation concepts along both behavior-structure and discrete-continuous lines. Throughout its exposition we point out the utility of the framework for addressing such issues as correctness of simulation programs, valid simplification of models, transformation of models from one formalism to another, and attaining higher levels of model validity.

Abstraction in methodology: A framework for computer support

Abstract: Computer-based methodologies for systems modelling, design, and analysis require the user to understand and manipulate abstractions of the objects of direct interest. The success of such methodologies may hang on human ability to deal with such abstractions and the degree to which the computer assistance meshes with this ability. This paper formulates systems methodologies within a problem solving frame-work in which abstractions, and the role they play, are formally represented. Two kinds of abstraction-based methodologies are distinguished: information-based methodologies employ abstractions to provide projections of the current state of the problem solving process, subsearch methodologies augment the underlying solution space with abstract representations that are intended to facilitate better perception of goal directions and improved quality of solutions. In this framework, implementation of abstraction classes is shown to involve overhead costs to both software and “brainware” that may vitiate the intended benefits. Components of, and approaches to, such a cost/benefit analysis are presented.

Structures for Model-Based Simulation Systems

Abstract: Model-based simulation support systems aim to provide comprehensive and integrated support of the activities comprising the modelling and simulation enterprise. This chapter discusses several formal structures underlying the design of such support systems including the composition tree, system entity structure, and experimental frame. An example based on Elzas1 model-based negotiation methodology is employed to illustrate the system-theoretic concepts under discussion.

Theory of discrete event specified models: modularity, hierarchy, experimental frames

Abstract: Representation mechanisms for discrete event simulation models are intended to facilitate the important conceptualization and communication components of model building science. Moreover, effective design of future computer-based decision support systems will rely upon well founded principles of model management. Modular and hierarchical concepts facilitate model building. This article extends the theory of discrete event system specification to provide a rigorous basis for modular and hierarchical simulation model construction. Practical applications of the theory are discussed and include programming constructs for modular and hierarchical simulation, inter-translation between modular and non-modular model description, and implementation of modular separation between model and experimental frame components of simulation programs.

Systems hierarchy as a basis for simulation model description

Abstract: This paper elaborates an integrated hierarchy of model description formalisms previously proposed. We discuss the advantages of the hierarchical approach vis a vis a standardized universal model description language. Among the principal advantages are the opportunities provided for concise model specification while at the same time enabling equivalence testing of models expressed in diverse formalisms.