An incredible volume of data is generated at a very high speed within the supply chain and it is necessary to understand, use and effectively apply the knowledge learned from analyzing data using intelligent business models.

However, practitioners and students in the field of supply chain management face a number of challenges when dealing with business models and mathematical modelling. Supply Chain Analytics and Modelling presents a range of business analytics models used within the supply chain to help readers develop knowledge on a variety of topics to overcome common issues.

Supply Chain Analytics and Modelling covers areas including supply chain planning, single and multi-objective optimization, demand forecasting, product allocations, end-to-end supply chain simulation, vehicle routing and scheduling models. Learning is supported by case studies of specialist software packages for each example. Readers will also be provided with a critical view on how supply chain management performance measurement systems have been developed and supported by reliable and accurate data available in the supply chain. Online resources including lecturer slides are available.

About the Author:

Nicoleta Tipi is Senior Lecturer in Operations and Supply Chain at the Open University, UK. She was previously Senior Lecturer at the University of Huddersfield where she gained experience lecturing in the area of supply chain modelling and logistics operations. Nicoleta Tipi has considerable industry experience, having worked in different roles involving modelling and analytics for Unilever.

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