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How to Test Your Models More Effectively: Applying Agile and Automated Techniques to Simulation Testing James T. Sawyer, David M. Brann. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

In the industrial engineering community, it’s a well-known adage that focusing on process can help achieve better results. In this second of a series of papers, we’ll focus on the process of simulation testing and outline how improving your testing process can lead to better results for your projects. We’ll consider model building as a software development exercise, and discuss how best practices from the broader software testing community can be applied for process improvement.
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Autonomic Self-Optimization According to Business Objectives Sarel Aiber, Dagan Gilat, Ariel Landau, Natalia Razinkov, Aviad Sela, and Segev Wasserkrug. International Conference on Autonomic Computing (ICAC'04), May 17 - 18, 2004, New York, New York, USA

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.
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IRS POST-FILING PROCESSES SIMULATION MODELING: A COMPARISON OF DES WITH ECONOMETRIC MICROSIMULATION IN TAX ADMINISTRATION Arnold Greenland, Erica Layne Morrison, David Connors, John L. Guyton, Michael Sebastiani, 2007 Winter Simulation Conference (WSC’07), Washington D.C., December 9-12, 2007

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.
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Java Engine for UML Based Hybrid State Machines Andrei V. Borshchev, Yuri B. Kolesov and Yuri B. Senichenkov. 2000 Winter Simulation Conference (WSC’00), December 10-13, 2000, Orlando, Florida, USA

One of the approaches to modeling hybrid systems is to assign algebraic-differential equations describing the continuous behavior to states of state machines that represent discrete logic. The resulting hybrid state machine is a powerful concept to specify complex interdependencies between discrete and continuous time behaviors. It, however, exposes the simulation engine to a number of problems, which we discuss. The hybrid state machine based approach presented in this paper is fully supported by UML-RT/Java tool TimeBroker developed at Experimental Object Technologies.
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Distributed simulation of hybrid systems with AnyLogic and HLA Andrei Borshchev, Yuri Karpov, and Vladimir Kharitonov. Future Generation Computer Systems Volume 18, Issue 6 (May 2002)

A large class of systems being developed has both continuous time and discrete time behavior. In fact, any system that interacts with physical world falls in that class. Chemical, Automotive, Military, Aerospace are areas most frequently mentioned in this respect. To model such systems successfully and to get accurate and reliable results from simulation experiments one needs an executable language naturally describing hybrid behavior, and a simulation engine capable of simulating discrete events interleaved with continuous time processes. Additional problems arise with simulating hybrid systems in a distributed environment.
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Multimethod Simulation Modeing using AnyLogic Andrei Borshchev, INFORMS Roundtable Meeting Fall 2007, Seattle, USA

The presentation shows you how to develop simulation models, choose abstraction level and methodology.
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