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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AnyLogic 4.0: Simulating Hybrid Systems with Extended UML-RT Andrei Borshchev. Simulation News Europe, No. 31 April 2001, pp 15-16

We outline a modelling approach aimed to capture sophisticated interdependencies of discrete and continuous behaviors in hybrid systems. The approach is essentially a hybrid extension of widely recognized object-oriented languages UML and UML-RT. It is fully supported by a new simulation tool AnyLogic 4.0 from Experimental Object Technologies.
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Modeling S-Class Car Seat Control with AnyLogic — Daimler-Chrysler Modeling Contest Alexei Filippov and Andrei Borshchev. Object-Oriented Modeling of Embedded Real-Time Systems (OMER-2), May 2001, Herrsching am Amersee, Germany, pp 46-50

In this paper we give an overview of the car seat model that was developed for Daimler-Chrysler modeling contest in year 2001 and was awarded the 1st prize. We outline the OO UML-RT based modeling approach that was used and the simulation tool AnyLogic that supports it, and discuss their main advantages with respect to automotive area.
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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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Decision Support Tool — Supply Chain Christian Wartha, Momtchil Peev, Andrei Borshchev, and Alexei Filippov. 2002 Winter Simulation Conference (WSC’02), December 8-11, 2002, San Diego, California, USA

We present a currently developed Decision Support Tool - Supply Chain (DST-SC). This is specialized domain oriented tool, which is an extension of the general purpose, UML-RT Hybrid Simulation kernel of AnyLogic by XJ Technologies. DST-SC allows high degree of flexibility with respect to the supply chain functionality being modeled, has the ability to handle large complex problems, and offers highly reusable model components, offering at the same time ease of use by non-experts in simulation.
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A Modern Simulation Approach for Pharmaceutical Portfolio Management Kirk Solo and Mark Paich. International Conference on Health Sciences Simulation (ICHSS'04), January 18 - 21, 2004, San Diego, California, USA

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.
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From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools Andrei Borshchev and Alexei Filippov. The 22nd International Conference of the System Dynamics Society, July 25 - 29, 2004, Oxford, England

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.
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A Methodological Framework for Business-Oriented Modeling of IT Infrastructure Ariel Landau, Segev Wasserkrug, Dagan Gilat, Natalia Razinkov, Aviad Sela, and Sarel Aiber. 2004 Winter Simulation Conference (WSC’04), December 5-8, Washington, D.C., USA

The creation of IT simulation models for uses such as capacity planning and optimization is becoming more and more widespread. Traditionally, the creation of such models required deep modeling and/or programming expertise, thus severely limiting their extensive use. Moreover, many modern intelligent tools now require simulation models in order to carry out their function. For these tools to be widely deployable, the derivation of simulation models must be made possible without requiring excessive technical knowledge.
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