Simulating Construction Bidding Using Agent-Based Modeling Sadegh Asgari, Ali Shafaat

Competitive bidding is the main mechanism for allocation of construction projects and consequently price determination of the construction services in the A/E/C industry. While different aspects of construction bidding have been studied in the literature, there is still a need for developing a comprehensive model that captures the complex dynamics of bidding environment by considering interactions among its components, most importantly construction contractors. This paper discusses the advantages of agent-based modeling in simulating the construction bidding process over the previously applied methodologies.
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Partial Paradigm Hiding and Reusability in Hybrid Simulation Modeling Using the Frameworks Health-DS and I7-Anyenergy A. Djanatliev, P. Bazan, R. German, University of Erlangen-Nuremberg. Winter Simulation Conference, 2014.

Many complex real-world problems which are difficult to understand can be solved by discrete or continuous simulation techniques, such as Discrete-Event-Simulation, Agent-Based-Simulation or System Dynamics. In recently published literature, various multilevel and large-scale hybrid simulation examples have been presented that combine different approaches in common environments.
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Modeling Country-Scale Electricity Demand Profiles M. Pruckner, D Eckhoff, R. German, University of Erlangen-Nuremberg. Winter Simulation Conference, 2014.

All over the world, and in particular in Germany, a trend toward a more sustainable electric energy supply
including energy efficiency and climate protection can be observed. Simulation models can support these
energy transitions by providing beneficial insights for the development of different electricity generation mix
strategies in future electric energy systems.
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An Agent-Based Explanation for 20th Century Living Situation Changes in America’s Severely and Persistently Mentally Ill Population Kyle L. Johnson, Dr. Dimitris Alevras, IBM Global Business Services; Dr. John Docherty, Dr. Erin Falconer, Otsuka Medical Affairs. AnyLogic Conference 2014

The largest public mental health facility in the United States is not a hospital; it is the Los Angeles County Jail. This paper describes an agent-based approach to explaining why prisons and jails house so many of America’s most seriously mentally ill. It traces this fact to the differing ways in which various housing situations react to mental illness and to legislation passed in the 1960’s, which allocated public funding away from state mental hospitals.
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Electric Vehicle Driver Simulation using Agent-Based Modeling Beaudry Kock, Recargo, Inc., 2014

Recargo has been developing an agent-based model with the AnyLogic tool to help us simulate the charging patterns of electric vehicle drivers in California. Our goal is to better understand the potential value from delivering electricity grid services with these vehicles. Development has only been underway for a few weeks, but in that time we’ve been able to use AnyLogic’s accessible interface and Java coding tools to quickly build and test a proof-of-concept model with which we can explore the potential for a more sophisticated and complex effort.
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The GAP-DRG Model: Simulation of Outpatient Care for Comparison of Different Reimbursement Schemes Patrick Einzinger, Niki Popper, Felix Breitenecker et al., Proceedings of the 2013 Winter Simulation Conference

In healthcare the reimbursement of medical providers is an important topic and can influence the overall outcome. We present the agent-based healthcare model, which allows a comparison of reimbursement schemes in outpatient care. It models patients and medical providers as agents. In the simulation of healthcare system, patients develop medical problems (i.e., diseases) and a need for medical services. This leads to utilization of medical providers. The reimbursement system receives information on the patients’ visits via its generic interface, which facilitates an easy replacement. We describe the assumptions of the model in detail and show how it makes extensive use of available Austrian routine care data for its parameterization. The model design is optimized for utilizing as much of these data as possible. However, many assumptions have to be simplifications. Further work and detailed comparisons with healthcare data will provide insight on which assumptions are valid descriptions of the real process.
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A Hybrid Simulation Model for Large-Scaled Electricity Generation Systems Marco Pruckner, Reinhard German, Proceedings of the 2013 Winter Simulation Conference

Due to the transition towards a sustainable energy supply, many electricity generation systems are faced with great challenges worldwide. Highly volatile renewable energy sources play an important role in the future electricity generation mix and should help compensate the phase-out of nuclear power in countries such as Germany. Simulation-based energy system analysis can support the conversion into a sustainable future energy system and are intended to find risks and miscalculations. In this paper we present main components of the electricity generation system models. We use a hybrid simulation approach with system dynamics and discrete event modules. This modular design allows quick model adoptions for different scenarios. Simulation results show the development of the future annual electricity balance, CO2 emission balance, electricty imports and exports, and the wholesale price of electricity.
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Prospective Healthcare Decision-Making By Combined System Dynamics, Discrete-Event And Agent-Based Simulation Anatoli Djanatliev, Reinhard German, Proceedings of the 2013 Winter Simulation Conference

Prospective Health Technology Assessment allows early decision making for innovative health care technologies. In our recent publications a hybrid simulation approach with System Dynamics and Agent-Based Modeling has been presented. This paper presents a mechanism to generate agents dynamically from SD models and extends the previously presented hybrid approach by process-oriented Discrete Event Simulation for hospital modeling.
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Modeling the Cycles of Gang and Criminal Behavior: Understanding the Social and Economic Influences Bruce Skarin, Jeanine Skorinko, Khalid Saeed, Oleg Pavlov, 27th International Conference of the System Dynamics Society, 2009

One of the challenges in developing policy for dealing with asocial behavior, such as burglary, vehicle theft, or violent crimes is the seemingly unpredictable rise and fall of activity. In retrospect these cycles in crime are often attributed to changes in factors such the size of a police force, level unemployment, or high school drop-out rate. What causes changes in these factors can some times be external to a local community, such as economic shifts affecting tax revenue, however many are internally linked. For example when crime is high, there is a call for more police and when crime is low, there is a justification for reducing the size of the force. Therefore, understanding how these factors are linked together as a whole may allow for better policies that reduce asocial behavior further and create more stability in the long term.
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Large Scale Healthcare Modeling by Hybrid Simulation Techniques using AnyLogic Anatoli Djanatliev and Reinhard German, Computer Networks and Communication Systems Department of Computer Science 7. Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques

This paper describes a methodical and practical approach of hybrid model creation using the simulation tool AnyLogic. We focus on general modeling aspects and on advanced techniques using a Level-Based Architecture that help to develop large scale hybrid simulation models. An implementation of a stroke therapy use-case and its simulation results will be discussed. Finally, some practical ideas for validation will be outlined, as we experienced during the stroke use-case development.
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