INFORMS Open Forum

Date and time: Nov 4 (Wed), 2020, 22:00 HKT (GMT+8)  [Local time]
Zoom link: https://hku.zoom.us/j/93965533071       Zoom meeting ID: 939 6553 3071

Seminar title: 
A Data-Driven Approach to Strategic Inventory Placement in Multi-Echelon Networks

Abstract: 
Supply chain networks heavily depend on reliable internal material flow for upholding process stability and cost-efficiency. Buffer stock needs to be strategically placed along intra-company and inter-company networks in order to guarantee service requirements despite demand uncertainty. The placement and sizing of safety stock poses a challenging, non-linear stochastic optimization problem. State-of-the art solution approaches require assumptions and estimation of demand distributions. We integrate recent advances in data-analytics and machine learning with inventory control theory to propose a data-driven optimization approach for safety stock planning in multi-echelon inventory networks based on the guaranteed service model. Errors from distributional assumptions and parameter estimation are reduced via a non-parametric approach based on actual historical demand data. Our model considers general (acyclic) multi-echelon networks, where each stage operates under a periodic review base stock policy. The model simultaneously determines safety stock allocation and sizing by setting base stocks for all stages under inventory holding cost minimization with respect to a service constraint. We use non-stockout probability and fill-rate service level constraints. The optimization problem is formulated as a mixed-integer linear program and solved with established mathematical programming solvers. In numerical experiments, we validate the applicability and solution quality of our approach on different network structures and case examples.

Speaker bio: 
Stefan Minner is a Full Professor for Logistics and Supply Chain Management at the School of Management, Technical University of Munich (TUM). His research interests are in global supply chain design, transportation optimization and inventory management and the work was published in many peer reviewed journals, including Management Science, Manufacturing & Service Operations Management, Operations Research, Production and Operations Management, Transportation Science, Transportation Research Part B, European Journal of Operational Research, Computers and Operations Research and OR Spectrum. He serves on several editorial boards of logistics and operations journals. Currently, Stefan Minner is the Editor-in-Chief of the International Journal of Production Economics. Stefan Minner is a fellow of the International Society for Inventory Research (ISIR) and is currently vice-chairman of the scientific advisory board of the German Logistics Association (BVL), and a member of the Research Committee of the European Logistics Association (ELA).

Date and time: Nov 4 (Wed), 2020, 22:00 HKT (GMT+8)  [Local time]
Zoom link: https://hku.zoom.us/j/93965533071       Zoom meeting ID: 939 6553 3071

Seminar title:
A Data-Driven Approach to Strategic Inventory Placement in Multi-Echelon Networks

Abstract:
Supply chain networks heavily depend on reliable internal material flow for upholding process stability and cost-efficiency. Buffer stock needs to be strategically placed along intra-company and inter-company networks in order to guarantee service requirements despite demand uncertainty. The placement and sizing of safety stock poses a challenging, non-linear stochastic optimization problem. State-of-the art solution approaches require assumptions and estimation of demand distributions. We integrate recent advances in data-analytics and machine learning with inventory control theory to propose a data-driven optimization approach for safety stock planning in multi-echelon inventory networks based on the guaranteed service model. Errors from distributional assumptions and parameter estimation are reduced via a non-parametric approach based on actual historical demand data. Our model considers general (acyclic) multi-echelon networks, where each stage operates under a periodic review base stock policy. The model simultaneously determines safety stock allocation and sizing by setting base stocks for all stages under inventory holding cost minimization with respect to a service constraint. We use non-stockout probability and fill-rate service level constraints. The optimization problem is formulated as a mixed-integer linear program and solved with established mathematical programming solvers. In numerical experiments, we validate the applicability and solution quality of our approach on different network structures and case examples.

Speaker bio:
Stefan Minner is a Full Professor for Logistics and Supply Chain Management at the School of Management, Technical University of Munich (TUM). His research interests are in global supply chain design, transportation optimization and inventory management and the work was published in many peer reviewed journals, including Management Science, Manufacturing & Service Operations Management, Operations Research, Production and Operations Management, Transportation Science, Transportation Research Part B, European Journal of Operational Research, Computers and Operations Research and OR Spectrum. He serves on several editorial boards of logistics and operations journals. Currently, Stefan Minner is the Editor-in-Chief of the International Journal of Production Economics. Stefan Minner is a fellow of the International Society for Inventory Research (ISIR) and is currently vice-chairman of the scientific advisory board of the German Logistics Association (BVL), and a member of the Research Committee of the European Logistics Association (ELA).