National Science Foundation awards grant to study multi-echelon inventory optimization
The grant, given to Manuel Rossetti, professor of industrial engineering at the University of Arkansas, supports research that transforms science and engineering studies into practical solutions that help the business community.
Supply chain management isn’t typically an area that would receive funding from the U.S. government's National Science Foundation (NSF), Arlington, Va. But, the agency awarded a $200,000 grant for research on multi-echelon inventory optimization.
The grant, given to Manuel Rossetti, professor of industrial engineering at the University of Arkansas, Fayetteville, Ark., is part of the NSF's "Partnerships for Innovation: Accelerating Innovation Research-Technology Transfer" program, which supports research that transforms science and engineering studies into practical solutions that help the business community.
Rosetti's project focuses on drawing on concepts developed in optimization and inventory segmentation research to help create software solutions that quickly optimize inventory levels within complex supply chains. Multi-echelon inventory optimization determines the correct allocation of inventory across a network based on demand variability at the various levels, or echelons, in the network (such as centralized distribution center, regional distribution center and retail store). It considers inventory levels holistically across the entire supply chain while taking into account the impact of inventories at any given point in the system.
Rosetti will be working with Invistics Corp., Peachtree Corners, Ga., to create software services that can analyze multi-echelon inventory segmentation, optimize inventory levels and perform fast "what-if" analysis. The research will focus on 1) discovering the best group size and criteria to use when applying segmentation analytics to large-scale industrial datasets; and 2) developing a software solution that best balances computational speed and solution quality.