Academic articles

A Simulation-Based Investigation of Freight Transportation Policy Planning and Supply Chains


Regional freight transportation policy planning is a difficult task, as few policy-planners have adequate tools to aid their understanding of how various policy formulations affect this complex, socio-technical system. In this paper, we develop a proof-of-concept model to simulate the impacts of public policies on freight transportation in a simulated region. We use the techniques of multi-disciplinary system design and optimization to analyze the formulation of regional freight transportation policies and examine the relative effects of policies and exogenous forces on the region in order to provide insight into the policy-planning process. Both single objective and multi-objective analysis is performed to provide policy-planners with a clear understanding of the trade-offs made in policy formulation.

Falling Off the Cliff? Increasing Economic Security for Low Income Adults as the Safety Net Shrinks


The public assistance system is supposed to offer a bridge between poverty and self-sufficiency. Families receive benefits such as Temporary Assistance for Needy Families (TANF) or Supplemental Nutrition Assistance Program (SNAP) to soften the impact of loss of income. The programs are intended to be limited in duration and provide a very modest amount of financial support. Some families are fortunate to also receive a housing voucher or a child care subsidy to help offset basic expenses. Eligibility for benefits varies by program and is based on different criteria, most of which are linked to personal income. This study asks: what happens when benefits are cut before individuals reach economic stability? This is frequently called the “benefits cliff.”

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.

Towards Closed Loop Modeling: Evaluatng The Prospects for Creating Recurrently Regrounded Aggregate Simulation Models Using Particle Filtering


Public health agencies traditionally rely heavily on epidemiological reporting for notifiable disease control, but increasingly apply simulation models for forecasting and to understand intervention tradeoffs. Unfortunately, such models traditionally lack capacity to easily incorporate information from epidemiological data feeds.

Increasing Rail Capacity Utilization in Port of Hamburg by Early Provision of Information for Import Containers


Various actors are involved in hinterland transportation of incoming rail containers along the maritime transport chain. To coordinate each actor’s logistics processes, and therefore to improve utilization of existing transport capacity, the early provision of information, e.g. in form of estimated time of arrival (ETA), is inevitable.

Quantitative Analysis of Bidding Strategies: A Hybrid Agent Based–System Dynamics Approach


Economic slowdown and construction demand shrinkage reduces the profit backlog for construction contractors and bites into their profit margin. The resulting fierce competition for jobs forces construction companies to look for more sophisticated analytical tools to analyze and improve their bidding strategies. For each contractor, bidding strategy is a decision-making process that is driven by the firm’s financial goals with the final objective of maximizing the firm’s gross profit and surpassing the breakeven point. This paper proposes a methodology to model and analyze different bidding strategies with hybrid agent based-system dynamics (ABSD) simulation.

Comparison between Individual-based and Aggregate Models in the context of Tuberculosis Transmission


The desire to better understand the transmission of infectious disease in the real world has motivated the representation of epidemic diffusion in the context of quantitative simulation. In recent decades, both individual-based (such as Agent-Based) models and aggregate models (such as System Dynamics) are widely used in epidemiological modeling. This paper compares the difference between system dynamics models and agent-based models in the context of Tuberculosis (TB) transmission, considering smoking as a risk factor.