Date: 17 April 2024, Wednesday
Time: 10.30 – 11.30
Place: MA-330
“A Random Model of Supply Chain Networks”
by
Philippe Blaetcchen
Bayes Business School
Abstract
Many optimization problems in supply chain management are formulated over graphs representing networks of interlinked supply chains. Solution approaches to these problems are often studied and tested on small, stylized supply chain networks, or on some of the few publicly available supply chain network dataset. This paucity of data means that fundamental questions about the relationship between the network structure and the properties of the problem solution such as quality and complexity are not addressed systematically.
Our paper fills this gap by introducing a random generative model of supply chain networks, in line with the computer science and social sciences literature, where random graph models are a popular tool for studying properties of “typical” networks. We show that our model, based on simple micro-foundations, generates network structures similar to those observed in practice. We propose that it supports (i) analyzing how network structure affects computational complexity, (ii) identifying new managerial insights, and (iii) benchmarking heuristics. We illustrate these benefits with a case study on safety stock optimization.
Bio
Philippe Blaettchen is an Assistant Professor in Management Analytics at Bayes Business School (formerly Cass) in London, and a Visiting Assistant Professor in Management Science and Operations at London Business School.
In his research, Philippe leverages novel analytical and computational tools to optimize the performance and sustainability of firms’ value creation and delivery processes. In particular, his research examines how new technologies can address operational and sustainability challenges that emerge due to the complexity of modern supply chains. Philippe’s work has been published in Management Science and Manufacturing & Service Operations Management, won the TIMES Best Dissertation Award, and was a finalist for the MSOM Society Award for Responsible Research in Operations Management.
Before starting at Bayes, Philippe earned his Ph.D. in Technology & Operations Management from INSEAD and his B.Sc. and M.Sc. in Industrial Engineering from Karlsruhe Institute of Technology in Germany.