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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Agent-based Analysis of Picker Blocking in Manual Order Picking Systems: Effects of Routing Combinations on Throughput Time Ralf Elbert, Torsten Franzke et al

Order picking is one of the most labor- and time-consuming processes in supply chains. Improving the performance of order picking is thus a frequently researched topic. Due to high cost pressure for warehouse managers the space in storage areas has to be used efficiently. Hence narrow-aisle warehouses where order pickers cannot pass as well as several order pickers working in the same area are common. This leads to congestion which is in this context referred to as picker blocking. This paper employs an agent-based simulation approach to investigate the effects of picker blocking in manual order picking systems with different combinations of routing policies for three order pickers in a rectangular warehouse with narrow-aisles.
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A Hybrid Simulation Framework for Integrated Management of Infrastructure Networks Mostafa Batouli, Ali Mostafavi, Florida International University. Winter Simulation Conference, 2014.

The objective of this paper is to propose and test a framework for integrated assessment of infrastructure systems at the interface between the dynamic behaviors of assets, agencies, and users. For the purpose of this study a hybrid agent-based/mathematical simulation model is created and tested using a numerical example related to a roadway network.
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Towards a Semiconductor Supply Chain Simulation Library (SCSC-SIMLIB) Jingjing Yuan, Thomas Ponsignon, Infineon Technologies AG. Winter Simulation Conference, 2014.

Simulation is a widely used technique for analyzing and managing supply chains. Simulation software packages offer standard libraries for selected functions and application areas. However, no commercial or freeware simulation tool proposes building blocks specific to semiconductor manufacturing.
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Comparing the Performance of Two Different Customer Order Behaviors Within the Hierarchical Production Planning Thomas Felberbauer, Klaus Altendorfer, University of Applied Sciences Upper Austria. Winter Simulation Conference, 2014.

A hierarchical production planning structure enables manufacturing systems to handle customer disturbances with different measures on different planning levels. Two different kinds of customer order behavior can be observed and are as well discussed in literature.
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Jobsite Logistic Simulation in Mechanized Tunneling M. Scheffer, T. Rahm, R. Duhme, M. Thewes, M. König, Ruhr-Universität Bochum. Winter Simulation Conference, 2014.

Projects in mechanized tunneling frequently do not reach their targeted production performance. Reasons are often related to an undersized or disturbed supply-chain management of the surface jobsite. Due to the sensitive interaction of production and logistic processes, planning and analyzing the supply-chain is a challenging task.
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Marine Logistics Decision Support for Operation and Maintenance of Offshore Wind Parks with a Multi Method Simulation Model Endrerud, Liyanage, and Keseric. Winter Simulation Conference, 2014.

The offshore wind industry in Europe is looking to move further from shore and increase the size of wind parks and wind turbines. As of now marine logistics during the operation and maintenance life cycle phase is, besides wind turbine reliability, the most important limitation for wind turbine service, repair and replacement, and pose a large risk for wind park operators and owners.
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Iterative Simulation and Optimization Approach for Job Shop Scheduling Ketki Kulkarni, Jayendran Venkateswaran, Indian Institute of Technology Bombay. Winter Simulation Conference, 2014.

In this paper, we present an iterative scheme integrating simulation with an optimization model, for solving
complex problems, viz., job shop scheduling. The classical job shop scheduling problem which is NP-Hard,
has often been modelled as Mixed-Integer Programming (MIP) model and solved using exact algorithms (for
example, branch-and-bound and branch-and-cut) or using meta-heuristics (for example, Genetic Algorithm,
Particle Swarm Optimization and Simulated Annealing).
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