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Dynamic Recovery Policies for Time-Critical Supply Chains under Conditions of Ripple Effect Dmitry Ivanov, Boris Sokolov, Inna Solovyeva et al.

We consider time critical supply chains in the Australia dairy industry and re-covery policies in the presence of the ripple effect. Ripple effect is the impact of a dis-ruption on supply chain economic performance and disruption-based scope of changes needed in the supply structures and parameters to preserve the resilience. First, we de-scribe the ripple effect in general and one example of the ripple effect in the dairy supply chain in Australia. Second, we present a model for reactive recovery policies in the dairy supply chain under conditions of the ripple effect and exemplify them on a simulation example. The results of this study can be used in future for comparing proactive and re-active approaches to tackling the ripple effect from resilience and flexibility views.
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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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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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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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