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The Urban Dynamics Educational Simulator: Tutorial for a Tool to Teach Agent-Based and Land Use and Transport Interactions Modeling Gonçalo Homem de Almeida Correia, Delft University of Technology

This paper describes a simple educational simulation tool to teach about agent-based modeling (ABM) and land use and transportation (LUT) interactions in urbanized regions. The relationship between land use and transportation in urban areas shows a dynamic complexity which is difficult to model with static or very aggregated approaches. Agent-based simulation is becoming a standard to model certain complex systems including LUT interactions. The LUT modeling with agent-based simulation has been evolving in the last 20 years and there are some complete models being applied to real metropolitan areas. In this paper, only some of the ingredients of those models are presented in an easy to explain agent-based model that can be used in classes.
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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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Simulation-based Single versus Dual Sourcing Analysis in the Supply Chain with Consideration of Capacity Disruptions, Big Data and Demand Patterns Dmitry Ivanov

Sourcing strategy analysis in the settings of supply chain flexibility in regard to single vs dual sourcing has been a well explored area over the last two decades. In recent years, single vs dual sourcing analy-sis has been increasingly introduced in supply chain disruption management. Since most of the deci-sion-support models for supply chain sourcing strategy adaptation in the case of disruptions presume real-time information and coordination, the issues of Big Data and business intelligence needs to be included into the consideration. A supply chain simulation model with consideration of capacity dis-ruption and Big Data along with experimental results are presented. Based on both literature analysis and modelling example, managerial insights are derived. A set of sensitivity experiments allows to illustrate the model’s behaviour. The analysis suggest recommendation on using single sourcing, ca-pacity flexibility, and dual sourcing for different combinations of demand and inventory patterns. The paper is concluded by summarizing the most important insights and outlining future research agenda.
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Simulation-based Ripple Effect Modelling in the Supply Chain Dmitry Ivanov

In light of low-frequency/high-impact disruptions, the ripple effect has recently been intro-duced into academic literature on supply chain management. The ripple effect in the supply chain results from disruption propagation from the initial disruption point to the supply, pro-duction and distribution networks. While optimization modelling dominates this research field, the potential of simulation modelling still remains under-explored. The objective of this study is to reveal research gaps that can be closed with the help of simulation modelling.
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