Charles R. Standridge

Performing simulation projects with The Extended Simulation System (TESS)

TESS, The Extended Simulation System, provides a comprehen sive, flexible and integrated framework for performing simula tion projects. Capabilities include (1) graphically building SLAM II networks and schematic models; (2) forms entry for simulation control information, simulation inputs, and anima tion specifications; (3) database management of user-defined data, model inputs and model outputs; (4) preparation of reports and graphs; (5) analysis of simulation results; and (6) the anima tion of simulation runs. A nonprocedural command language provides access to the graphical builders and forms system as well as selects data for reports, graphs, analysis or animation. In addition, a library of subroutines gives the programmer ac cess to all data in the TESS database. The TESS project framework consists of nine elements of a proj ect and three functions for operating on these elements. Integra tion is based on a single, central database containing all element occurrences. A comprehensive example illustrates the problem- solving procedures possible with TESS.

Using Expert Systems for Simulation Modeling of Patient Scheduling

Modeling the scheduling of patient appointments is an important issue in simulating a health care delivery facility. A simulation model must in clude the control logic of appointment scheduling software and the explicit and implicit decision rules used by the human scheduler in selecting an appointment time. Expert systems provide one way of modeling such control logic and decision rules. We describe a structure for an expert sys tem that models patient appointment scheduling and the integration of such an expert system within a simulation model. An example expert system for a small animal veterinary clinic is presented.

A veterinary practice simulator based on the integration of expert system and process modeling

Health care delivery systems of all kinds must operate under resource constraints. This gives rise to design issues that are best addressed by engineering methods such as simulation modeling and analysis. A simulator to help deal with veterinary practice design, planning, and operation issues has been developed. An expert system for processing patient appointments was integrated with traditional process world view modeling capabilities to produce the simulator. Simulator input variables and performance measures are described. An example application in practice operation and design, including extensive statistical analysis, is presented.

Using SLAM and SDL to assess space shuttle experiments

New tools simplify the development and simulation of models as well as the analysis and presentation of simulation results. The SLAM language allows the modeler to use network, dis crete event and continuous modeling prospectives in any combination to describe the different parts of a system. The SDL database management system allows the modeler to col lect simulation results, and at the same time to analyze and present these results independent of the simulation run. We applied SLAM and SDL in analyzing a package of experi ments for the Space Shuttle. The SLAM model of the experi mental package shows the utility of a combined network, discrete event, and continuous model. The SDL database illustrates the advantages of storing model run results, using the computer in comparing alternatives, defining and comput ing performance measures after simulation results are made, and generating reports and plots of model results in the data base. The results of our analysis were also of interest. Only a limited amount shuttle resources could be used by the package of ex periments. Thus, the simulation was used to determine the amount of memory needed for each experiment and for the microprocessor, as well as the reasons for the transmission delay for data from each experiment.

Issues in the development of a model for planning health manpower

This paper describes the development of a GASP IV simulation of the primary health-care system of Indiana. In the course of this research, other prob lems were found to be as important as the construc tion of the model. These problems included data acquisition and analysis, definition of system per formance measures, the comparison of alternative policies, and the interaction between physicians and system analysts.

Software aids for simulation

Simulation professionals have recently again focused on the need to divide simulation activities into independent stages, including model formulation and description, program development, model execution, verification, validation, and analysis and presentation of results. The widespread availability of inexpensive computing power now allows computer assistance in each stage. While simulation languages help with program development, new kinds of software are necessary for the other stages. This new software can be referred to as simulation support software.

A method for computing discrete event simulation performance measures from traces

Interactive simulation systems supporting the post-simulation analysis, presentation and interpretation of results have been developed and will continue to evolve. Post- simulation definition and computation of performance measures should be one important capability of such systems. We propose a method for accomplishing this objective. A simulation language neutral form of a discrete event trace contains the information from which the performance measures are computed. Computational procedures for typical performance measures: transaction time delays, numbers of transactions concurrently engaged in an activity or in a queue, time intervals between occurrences of the same event, and the state distribution of resource units are given. A software library for managing traces and performing the needed computations is described. An example shows an illustrative application of the method to three simulation languages: SLAM II, GPSS, and INSIGHT.

RSMM: A network language for modeling pollutants in river systems:

Predicting the steady state distribution of pollutants in rivers is important for water quality managers. A new simulation lan guage, the River System Modeling Methodology (RSMM), helps users construct simulation models for analyzing river pollution. In RSMM, a network of nodes and branches represents a river system. Nodes represent elements such as junctions, dams, withdrawals, and pollutant sources; branches represent homo geneous river segments, or reaches. The RSMM processor is a GASP V program. Models can employ either the embedded Streeter-Phelps equations or user supplied equations. The user describes the network diagram with GASP- like input cards. RSMM outputs may be printed or stored in an SDL™* database. An interface between SDL and DISSPLA provides high quality graphical output.