Richard E. Nance

A history of discrete event simulation programming languages

The history of simulation programming languages is organized as a progression in periods of similar developments. The five periods, spanning 1955-1986, are labeled: The Period Search (1955-1960); The Advent (1961-1965); The Formative Period (1966-1970); The Expansional Period (1971-1978), and The Period of Consolidation and Regeneration (1979-1986). The focus is on recognizing the people and places that have made important contributions in addition to the nature of the contribution. A balance between comprehensive and in-depth treatment has been reached by providing more detailed description of those languages which have or have had major use. Over 30 languages are mentioned, and numerous variations are described in the major contributors. A concluding summary notes the concepts and techniques either originating with simulation programming languages or given significant visibility by them.

Perspectives on the Evolution of Simulation

Simulation is introduced in terms of its different forms and uses, but the focus on discrete event modeling for systems analysis is dominant as it has been during the evolution of the technique within operations research and the management sciences. This evolutionary trace of over almost fifty years notes the importance of bidirectional influences with computer science, probability and statistics, and mathematics. No area within the scope of operations research and the management sciences has been affected more by advances in computing technology than simulation. This assertion is affirmed in the review of progress in those technical areas that collectively define the art and science of simulation. A holistic description of the field must include the roles of professional societies, conferences and symposia, and publications. The closing citation of a scientific value judgment from over 30 years in the past hopefully provides a stimulus for contemplating what lies ahead in the next 50 years.

A specification language to assist in analysis of discrete event simulation models

Effective development environments for discrete event simulation models should reduce development costs and improve model performance. A model specification language used in a model development environment is defined. This approach is intended to reduce modeling costs by interposing an intermediate form between a conceptual model (the model as it exists in the mind of the modeler) and an executable representation of that model. As a model specification is constructed, the incomplete specification can be analyzed to detect some types of errors and to provide some types of model documentation. The primitives used in this specification language, called a condition specification (CS), are carefully defined. A specification for the classical patrolling repairman model is used to illustrate this language. Some possible diagnostics and some untestable model specification properties, based on such a representation, are summarized.

Simulation model reuse: definitions, benefits and obstacles

Abstract The term ‘simulation model reuse’ can be taken to mean various things from the reuse of small portions of code, through component reuse, to the reuse of complete models. On a more abstract level, component design, model design and modelling knowledge are prime candidates for reuse. The reuse of simulation models is especially appealing, based on the intuitive argument that it should reduce the time and cost for model development. In a discussion with four simulation modelling experts, however, a number of issues were raised that mean these benefits may not be obtainable. These issues include the motivation to develop reusable models, the validity and credibility of models to be reused, and the cost and time for familiarisation. An alternative simulation methodology was proposed, that may lend itself better to model reuse.

The Conical Methodology and the evolution of simulation model development

Originating with ideas generated in the mid-1970s, the Conical Methodology (CM) is the oldest procedural approach to simulation model development. This evolutionary overview describes the principles underlying the CM, the environment structured according to these principles, and the capabilities for large complex simulation modeling tasks not provided in textbook descriptions. The CM is an object-oriented, hierarchical specification language that iteratively prescribes object attributes in a definitional phase that is topdown, followed by a specification phase that is bottom-up. The intent is to develop successive model representations at various levels of abstraction that can be diagnosed for correctness, completeness, consistency, and other characteristics prior to implementation as an executable program. Related or competitive approaches, throughout the evolutionary period are categorized as emanating from: artificial intelligence, mathematical programming, software engineering, conceptual modeling, systems theory, logic-based theory, or graph theory. Work in each category is briefly described.

Web-based simulation: revolution or evolution?

The nature of the emerging field of web-based simulation is examined in terms of its relationship to the fundamental aspects of simulation research and practice. The presentation, assuming a form of debate, is based on a panel session held at the first International Conference on Web-Based Modeling and Simulation, which was sponsored by the Society for Computer Simulation during 11-14 January 1998 in San Diego, California. While no clear “winner” is evident in this debate, the issues raised here certainly merit ongoing attention and contemplation.

Expanding our horizons in verification, validation, and accreditation research and practice

Many different types of modeling and simulation (M&S) applications, consisting of a combination of software, hardware, and humanware, are used in dozens of disciplines under diverse objectives including acquisition, analysis, education, entertainment, research, and training. Certification of sufficient accuracy of an M&S application by conducting verification, validation, and accreditation (VV&A) requires multifaceted knowledge and experience, and poses substantial technical and managerial challenges for researchers, practitioners, and managers. The challenges can only be met by using a very broad spectrum of approaches and expanding our horizons in VV&A. This paper presents 13 strategic directions to meet those challenges. The strategic directions provide guidelines for successful VV&A research and practice.

A collaborative evaluation environment for credibility assessment of modeling and simulation applications

Credibility assessment of modeling and simulation (M&S) applications is becoming increasingly more important as M&S applications are used more and more for complex system design evaluation, M&S-based acquisition, problem solving, military training, and critical decision making. M&S credibility assessment is a very complex process, involves the measurement and evaluation of hundreds of qualitative and quantitative elements, mandates subject matter expert evaluation, and requires the integration of disparate measurements and evaluations. Planning and managing such measurements and evaluations require a unifying methodology and should not be performed in an ad hoc manner. We have developed such a methodology, which can be used for credibility assessment of any kind of M&S application. To provide computer-aided assistance in applying our methodology and to enable collaborative evaluations by geographically dispersed people, we have developed a Web-based client/server software system. This tutorial introduces our software system, which can be used at or .

A Comparison Of Selected Conceptual Frameworks For Simulation Modeling

The purpose of this paper is to compare thirteen Conceptual Frameworks (CFs) selected from among several categories of applicability to discrete-event simulation modeling. Each CF is briefly reviewed to provide the background information required for the comparison. Based on the insights gained in applying the CFs to the modeling of a complex traffic intersection system, the CFs are compared relative to their distinct characteristics and capabilities. Comparative comments are grouped according to the design guidance and implementation guidance features of the CFs. Conclusions highlight the inadequacies of the CFs and the importance of research in CF development.

Parallel discrete event simulation: a modeling methodological perspective

The field of parallel discrete event simulation is entering a period of self-assessment. Fifteen years of investigation has seen great strides in techniques for efficiently executing discrete event simulations on parallel and distributed machines. Still, the discrete event simulation community at large has failed to recognize much of these results. One reason for this is perhaps a disagreement in the focus and purpose of the parallel discrete event simulation research community (primarily computer scientists) and the discrete event simulation community (a widely diverse group including operations researchers, statisticians, as well as computer scientists). An examination of the parallel discrete event simulation problem from a modeling methodological perspective illustrates some of these differences and reveals potentials for their resolution.