Blog

Disaster Response Applications Using Agent-Based Modeling


Disaster Response Applications Using Agent-Based Modeling

Battelle is the world’s largest, non-profit, independent R&D organization, and is a worldwide leader in the development, commercialization, and transfer of technology. They manage or co-manage laboratories for the U.S. Department of Energy, the U.S. Department of Homeland Security, and an international nuclear laboratory in the United Kingdom. Battelle developed a disaster response solution for a federal government agency using AnyLogic, and in particular, agent-based modeling due to its multimethod capabilities. Joe Simkins, Economist at Battelle shared the solution with the AnyLogic community during the AnyLogic Conference 2013 in Washington D.C. Joe works in the fields of applied microeconomics, emergent simulation, and behavioral economics with experience in a wide variety of project applications ranging from health care to disaster response.

Find Optimal Product Sampling Using Agent-Based Modeling


Find Optimal Product Sampling Using Agent-Based Modeling

Before launching a new drug, a pharmaceutical company should decide the optimal promotional mix for both patient and doctors, and the optimal sampling level, high enough to induce therapy without cannibalizing paid prescriptions. Using AnyLogic Simulation Modeling, JP Tsang, Ph.D. & MBA, addresses the complexities of launching a new drug in the pharmaceutical industry, the need for a Contract Sales Organization (CSO) and the influence of Key Opinion Leaders (KOL). The project zeroed in on the medical group practice in order to better understand the dynamics between physician and patient, and between physician and medical representatives. The Agent Based Model (ABM) allows you to understand local behavior, identify bottlenecks regarding certain output variables and better grasp the big picture.

Agent-Based Model for the Secondary Threat Resulting from a Ballistic Impact Event


Agent-Based Model for the Secondary Threat Resulting from a Ballistic Impact Event

The process by which a high-velocity impact event leads to fire ignition onboard military vehicles is complex, influenced by the interaction of heated debris fragments and fuel spurting from ruptured tanks. Matthew J. Bova of the University of Cincinnati, Frank W. Ciarallo of Wright State University, and Raymond R. Hill of the Airforce Institute of Technology completed a proof-of-concept project involving the secondary threat resulting from a ballistic impact event using agent-based modeling in AnyLogic. Developing a complete characterization of the secondary threat resulting from a high-velocity projectile impact on the exterior of an aircraft body is of particular concern to the aircraft survivability community. Such ballistic impacts typically result in penetration of the body, generating clouds of debris fragments and releasing large quantities of thermal energy.

Simulation Modeling Based on Routine Healthcare Data


Simulation Modeling Based on Routine Healthcare Data

Decisions made by health care professionals require tools for planning, testing and assessment of new technologies or interventions. The complex structures, interactions and processes involved in health care, make change and innovation an ongoing challenge. Patrick Einzinger and Christoph Urach from DWH Simulation Services and Vienna University of Technology in partnership with the Austrian Association of Social Insurances (AASI) were given an opportunity to analyze public data for the purpose of critical future decision making. The AASI assembled routine care data upon reimbursement of heath care providers, which includes drugs prescribed, services rendered and diagnosis. Typical statistics and mathematical modeling were considered as a tool to analyze the data, but simulation was chosen to ensure the mass amount of data could be fully utilized, thus increasing the accuracy of the analysis and results.

What’s New in AnyLogic 7? Agent-Based Modeling Enhancements


What’s New in AnyLogic 7? Agent-Based Modeling Enhancements

“The Great Merge.” Most likely this is a familiar term, but perhaps you haven’t been able to experience the idea quite yet, or are not familiar with the many benefits “The Great Merge” permits. Let us take a moment to expand upon “The Great Merge,” other Agent-Based modeling enhancements, and what these changes mean for future model building. “The Great Merge,” in summary, is an ultimate unification of agents, entities, resources, pedestrians, trains, etc. and is useful to modelers in a multitude of ways. Read through the following list to familiarize yourself with the new developments.

Why Use Multimethod Modeling?


Why Use Multimethod Modeling?

AnyLogic multimethod or multi-paradigm simulation gives you the opportunity to choose the most efficient method or a combination, in order to best address your problem. Whether you are familiar with one or more modeling paradigms, or new to modeling and simulation, employing multimethod modeling capabilities will enhance business process optimization, strategic planning, forecasting and beyond. Let us first take a look into each paradigm and where they are best utilized, then explain where multimethod modeling fits and how it can improve your modeling process and simulation results.

Agent Based Models Trending at WinterSim 2013


Agent Based Models Trending at WinterSim 2013

Industry leaders are realizing the benefits of Agent Based Modeling with AnyLogic software. In the dynamic and complex market environments of telecommunications, insurance, epidemiology, and healthcare, consumers make choices based on the characteristics of the consumers themselves and other factors that are best captured by the agent based modeling paradigm. Individual-centric data from Customer Relationship Management systems can be used to parameterize the model agents. The number of papers published for WinterSim 2013 using Agent Based Models nearly doubled from that of 2012. See how industry leaders are putting CRM, ERP and other big data to work using Agent Based Models.

Can one make precise forecasts of consumer behavior?


Can one make precise forecasts of consumer behavior?

Many people, who are interested in sales forecasting, are familiar with the book Predictably Irrational by Dan Ariely. The abstract of the book states: “Dan Ariely refutes the common assumption that we behave in fundamentally rational ways. From drinking coffee to losing weight, from buying a car to choosing a romantic partner, we consistently overpay, underestimate, and procrastinate. Yet these misguided behaviors are neither random nor senseless. They're systematic and predictable—making us predictably irrational.” The irrationality of human decisions is the basis of behavioral economics. Predictably Irrational, and many other books, give many examples which argue the idea of consumer rationality. Businesses are irrational too, as they are guided by human beings.

AnyLogic North America Attends Agent-Based Modeling Bootcamp for Health Researchers


AnyLogic North America was to take part in Dr. Nate Osgood’s 3rd Annual Agent-Based Modeling Bootcamp for Health Researchers last week at the University of Saskatchewan in Saskatoon, SK, Canada. Dr. Osgood’s platform of choice is AnyLogic for many reasons, not least the graphical nature of the editor, the excellent support offered by The AnyLogic Company, and the software’s multimethod capabilities. The bootcamp was attended by roughly 25 people, most of them academicians, with a high proportion of them interested in epidemiology. However, according to Dr. Osgood, a large proportion of attendees indicated that multimethod modeling was an item of high interest to them, and he adjusted the course content accordingly.