Towards Supply Chain Risk Analytics Fundamentals, Simulation, Optimization /

In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics. She transfers the newly defined concepts for the modelling and operationalization of supply chain risk within simulation and optimization approaches, in order to ease unexpected deviations and disrupti...

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Bibliographic Details
Main Author: Heckmann, Iris (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Gabler, 2016.
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Online Access: Full text (Wentworth users only)

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505 0 |a A New Definition of Supply Chain Risk -- Supply Chain Risk Analysis.– Common Flaws, Core Areas, and Main Tasks -- A Simulation-based Approach for Supply Chain Risk Analysis (SimSCRF) -- A Real Case Evaluation of the SimSCRF Approach -- Embedding Comprehensive Risk in Supply Chain Network Design Models. 
520 |a In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics. She transfers the newly defined concepts for the modelling and operationalization of supply chain risk within simulation and optimization approaches, in order to ease unexpected deviations and disruptions, which are subsumed under the notion of supply chain risk, increasingly aggravating the planning and optimization of supply chains. Content • A New Definition of Supply Chain Risk • Supply Chain Risk Analysis – Common Flaws, Core Areas, and Main Tasks • A Simulation-based Approach for Supply Chain Risk Analysis (SimSCRF) • A Real Case Evaluation of the SimSCRF Approach • Embedding Comprehensive Risk in Supply Chain Network Design Models Target Groups • Lecturers and students of management and operations research • Professionals in the field of supply chain management, supply chain planning, risk management About the Author Iris Heckmann started as a research scientist at the FZI Research Centre for Information Technology in Karlsruhe and headed the department of Risk-aware Logistics: Supply Chain and Health. Since April 2016 she is division head of the research division Information Process Engineering. Her research focuses on developing mathematical optimization approaches for supply chain risk analytics. 
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