Agent-Based Simulation for Dual Toll Pricing of Hazardous Material Transportation

A dual toll pricing is a conceptual policy in which policy maker imposes toll on both hazardous materials (hazmat) vehicles as well as regular vehicles for using populated road segments to mitigate a risk of hazmat transportation. It intends to separate the hazmat traffic flow from the regular traffic flow via controlling the dual toll. In order to design the dual toll pricing policy on a highly realistic road network environment and detailed human behaviors, an extended Belief-Desire-Intention (BDI) framework is employed to mimic human decision behaviors in great detail. The proposed approach is implemented in AnyLogic agent based simulation software with using a traffic data of Albany, NY. Also, search algorithms in OptQuest are used to determine the optimum dual toll pricing policy which results in the minimum risk and travel cost based on the simulation results. The result reveals the effectiveness of the proposed approach in devising a reli-able policy under the realistic road network conditions.

The GAP-DRG Model: Simulation of Outpatient Care for Comparison of Different Reimbursement Schemes

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.

Agent-Based Simulation of a Tuberculosis Epidemic

We propose an epidemic agent-based simulation model for disease (TB) transmission dynamics study and to find out the role of various contact networks. Our model simulates the TB epidemic course across a single population and uses a hierarchical network of contacts in three levels, typical to the transmission of airborne diseases (Mossong et al. 2005). Parameters are chosen from the literature, and the model is calibrated to a setting of high TB incidence. We use our model to study the transmission dynamics at an individual level with regard to the timing and distribution of secondary infections from a single source. The average time for disease diffusion to reach 50% of infections at an individual level is estimated, and the timing patterns are compared among different networks. We perform sensitivity analysis of results with regard to multiple parameter values, and discuss the implications for TB control policy.

West Nile Virus System Dynamics Investigation In Dallas County, TX

After its first introduction in 1999, West Nile Virus (WNV) has spread very widely along the east coasts of the United States before appearing in Texas where 1792 cases were reported of which 82 were fatal in 2012. The interesting patterns and behavior of the virus and its amplified impact on the county of Dallas drove this work. This paper encompasses a thorough development of a systems dynamics simulation model of virus's infectious behavior and dynamics in Dallas County, TX utilizing historical data collected and the aid of suitable software packages.

A Hybrid Simulation Model for Large-Scaled Electricity Generation Systems

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.

Communication Modeling for a Combat Simulation in a Network Centric Warfare Environment

Effective and efficient information sharing in a warfare environment is a key feature of the Network Centric Warfare (NCW) concept, and a combat simulation model should reflect this key feature. Most existing combat simulation models adopt a simplified communication model, which may lead to overestimating an actual level of communication performance. On the other hand, while providing accurate assessment of communication performance, a low-level, detailed, engineered model for communication tends to be overly sophisticated and computationally intensive to incorporate in typical combat models. In this paper, we propose a communication model in the context of an engagement-level of NCW combat simulation. In particular, we use a propagation loss model to determine a success or failure of individual communication attempts. We also define a set of model parameters to characterize various communication networks deployed in a battlefield. Preliminary simulation experiments and their results are presented to illustrate the proposed modeling framework

Distortion of “Mental Maps” as an Exemplar of Imperfect Situation Awareness

This paper provides the first results of dissertation research that seeks to develop and apply an experimental milieu for the study of imperfect Situation Awareness/Situation Understanding (SA/SU) and of decision-making based on that SA/SU. It describes an agent-based simulation and initial results of simulation experiments conducted with that framework. The simulation experiments explore a specific, easily understood, and quantifiable example of human behavior: intelligent agents being spatially “lost” while trying to navigate in a simulation world.

An Online Simulation To Link Asset Condition Monitoring And Operations Decisions In Through-Life Engineering Services

This paper presents an online simulation framework that can be used to support operational decisions within the context of Through-life Engineering Services. Acting as a closed-loop feedback control mechanism, the simulation model is physically coupled to the assets and will be triggered and automatically executed to assess a set of operational decisions related to maintenance scheduling, resource allocation, spare parts inventory etc. Experimental cases comparing the online simulation against the traditional approach will also be presented. The outcomes have demonstrated the prospects of the framework in enabling more effective/efficient operations of engineering services leading to high assets availability and reduced through-life costs.

A Modular Simulation Model For Assessing Interventions For Abdominal Aortic Aneurysms

This paper discusses the development of an individual based simulation of interventions for better treatment of patients with abdominal aortic aneurysms (AAA). The interdisciplinary subject required collaboration of medical doctors, Health Technology Assessment (HTA) experts and modelers.

Prospective Healthcare Decision-Making By Combined System Dynamics, Discrete-Event And Agent-Based Simulation

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.