Emergency Departments (EDs) require advanced support systems for monitoring and controlling their processes: clinical, operational, and financial. A prerequisite for such a system is comprehensive operational information (e.g. queueing times, busy resources,…), reliably portraying and predicting ED status as it evolves in time. To this end, simulation comes to the rescue, through a two-step procedure that is hereby proposed for supporting real-time ED control.
Current IT related optimization efforts focus on optimizing IT level metrics such as response times, availability, etc. What the business requires is that such IT optimization be carried out so as to optimize business objectives. Such optimization is not a one-time effort as there may be significant changes, (e.g. server failures, sudden increase in the number of users) that may render any existing policy sub-optimal. Such optimization can be led in AnyLogic.
IRS Office of Research Headquarters measures and models taxpayer burden, defined as expenditures of time and money by taxpayers to comply with the federal tax system. In this research activity, IRS created two microsimulation models using econometric techniques to enable the Service to produce annual estimates of taxpayer compliance burden for individual and small business populations. Additionally, a Discrete Event Simulation (DES) model was developed to represent taxpayer activities and IRS administration in postfiling processes.
By creating an integrated simulation environment that models the underlying structure of a pharmaceutical enterprise portfolio it becomes possible to identify the optimal longitudinal allocation of finite resources across the constellation of available investment opportunities. The implementation of a hybrid approach that integrates multiple modeling techniques and analytic disciplines allows for a comprehensive environment that captures the underlying dynamics that drive observed market behavior. The implementation of an object oriented model structure constrains the models complexity by supporting dynamic re-use of both structure and logic.
This article discusses General Motors’ North American Enterprise Model, a system dynamics model of the entire North American automobile market. The Enterprise Model takes a broad look across the corporation and its marketplace, combining internal activities such as engineering, manufacturing and marketing with external factors such as competition for consumer purchases in the new and used vehicle marketplaces. Eight groups of manufacturers compete monthly for a decade across eighteen vehicle segments, making segment-by-segment decisions about price, volume and investment.
This paper may be considered as a practical reference for those who wish to add (now sufficiently matured) Agent Based modeling to their analysis toolkit and may or may not have some System Dynamics or Discrete Event modeling background. We focus on systems that contain large numbers of active objects (people, business units, animals, vehicles, or even things like projects, stocks, products, etc. that have timing, event ordering or other kind of individual behavior associated with them). We compare the three major paradigms in simulation modeling: System Dynamics, Discrete Event and Agent Based Modeling with respect to how they approach such systems. We show in detail how an Agent Based model can be built from an existing System Dynamics or a Discrete Event model and then show how easily it can be further enhanced to capture much more complicated behavior, dependencies and interactions thus providing for deeper insight in the system being modeled.
This paper explores the problem of fragmenting social networks enabled by spatial distancing between distinct socioeconomic classes. Such fragmentation is evidenced by the experience of urban sprawl without population growth. We develop a prototype model to examine the spatial dynamics of social network evolution in the face of neighborhood migration. This model draws upon the small world analogy by using an initial template of connections that are “rewired” over time. Spatially, connections are established for neighborhood proximity. Socially, connections are added based upon similarity of economic class.
System Dynamics, has been useful for a variety of disciplines; however, it has limitations in showing a geographical representation of the models under study. This paper proposes a methodology based on layered vectors which allows the use a city’s census information to feed a Geographic Information System (GIS). The GIS objects implemented into System Dynamics and located at coordinates X.Y.Z become the entry parameters for the simulation.
The objective of this paper was to determine the effects of adding a healthcare provider in triage on average length of stay (LOS) and proportion of patients with >6 h LOS. The other goal was to assess the accuracy of computer simulation in predicting the magnitude of such effects on these metrics.