Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Learning from the aggregated optimum: decision rules for managing ameliorating food inventory
Alexander Pahr1, Martin Grunow1, Pedro Amorim2
1Technical University of Munich, Germany; 2INESC TEC, Faculty of Engineering of University of Porto, Portugal
The management of ameliorating food inventories with age-differentiated products entails a trade-off between immediate revenues and further maturation. We derive interpretable decision rules for purchasing, fulfilment, and issuance decisions under purchase price and decay uncertainty. We learn the rules from the optimal policy for an aggregated problem. A linear program facilitates scaling back. For a port wine industry case, our derived management strategies yield a substantial profit increase.
Fixing inventory inaccuracies at scale
Vivek F Farias1, Andrew A Li2, Tianyi Peng1
1MIT; 2CMU
We observe that detecting inventory inaccuracies can be viewed as a problem of identifying anomalies in a (low-rank) Poisson matrix. We propose a conceptually simple approach whose cost approaches that of an optimal algorithm at a min-max optimal rate. Using data from a consumer goods retailer, we show that our approach provides up to a 10× cost reduction over incumbent approaches to anomaly detection.
