Academic articles

Simulation testbed for the analysis of beneficial business strategies for the airbus A350 production ramp-up


The production ramp-up of new aircraft is characterized by high complexity and planning and control chal-lenges caused by complex product design, supply chain and production processes. In the past, this resulted in significant delays and increased costs of the production ramp-up. Novel business strategies and planning and scheduling technologies promise better production control and risk mitigation during the ramp-up phase. The European research project ARUM has developed those business strategies and a new distributed decision support solution based on knowledge processing technologies. A simulation testbed was used to identify the most beneficial business strategies and to evaluate linked control strategies for the industrial use case of the Airbus A350 production ramp-up. This paper discusses the potential of simulations for the business strategy definition and for the validation of linked control strategies from the industrial end-user perspective.

A discrete event simulation model of the Viennese subway system for decision support and strategic planning


In this paper, we present a discrete event simulation model of the Viennese subway network with capacity constraints and time-dependent demand. Demand, passenger transfer and travel times as well as vehicle travel and turning maneuver times are stochastic. Capacity restrictions apply to the number of waiting passengers on a platform and within a vehicle. Passenger generation is a time-dependent Poisson process which uses hourly origin-destination-matrices based on mobile phone data. A statistical analysis of vehicle data revealed that vehicle inter-station travel times are not time- but direction-dependent. The purpose of this model is to support strategic decision making by performing what-if-scenarios to gain managerial insights. Such decisions involve how many vehicles may be needed to achieve certain headways and what are the consequences. There are trade-offs between customer satisfaction (e.g. travel time) and the transportation system provider’s view (e.g. mileage). First results allow for a bottleneck and a sensitivity analysis.

Dynamic Recovery Policies for Time-Critical Supply Chains under Conditions of Ripple Effect


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.

Strategic Planning of Logistics for Offshore Arctic Drilling Platforms Supported by Simulation


The operation of offshore drilling platforms requires a lot of logistics: supply of platforms by platform supply vessels (PSVs), backward transportation of waste in containers and transportation of oil by tankers to export ports. The severe weather conditions of the Arctic Ocean increase the number of possible disruptions that influence the logistic system. The operation of PSVs and tankers has multiple constraints and interactions. An agent-based simulation has been developed in AnyLogic to support the strategic planning of logistics by year 2042. The presentation discusses the use of the model to determine the required number of vessels and compare different options of crude oil outbound logistic network design.

Partial Paradigm Hiding and Reusability in Hybrid Simulation Modeling Using the Frameworks Health-DS and I7-Anyenergy


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.

Modeling Country-Scale Electricity Demand Profiles


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.

An Agent-Based Explanation for 20th Century Living Situation Changes in America’s Severely and Persistently Mentally Ill Population


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.

Electric Vehicle Driver Simulation using Agent-Based Modeling


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.

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.

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.


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