Category: News

The H. Milton Stewart School of Industrial and Systems Engineering (ISyE) announced that A. Russell Chandler III Chair and Professor Pascal Van Hentenryck has assumed the role of associate chair for innovation and entrepreneurship (ACIE). This is a new position within ISyE’s leadership structure. See this full announcement.

Check our paper on unit commitment for electrical and gas networks. It presents a way to avoid reliability issues during major events, like the polar vortex events. This paper benefited from some really insightful comments from reviewers.

 

Check this article out for the wonderful Seth Bonder Camp we are teaching every year.

 

Check our recent papers on differential privacy for census data, time series, and energy systems.

•  Differential Privacy for Power Grid Obfuscation. Fernandino Fioretto, Terrence Mak, and Pascal Van Hentenryck. IEEE Transactions on Smart Grids.
• OptStream: Releasing Time Series Privately. Ferdinando Fioretto and Pascal Van Hentenryck, Journal of Artificial Intelligence Research (JAIR), 65, 423–456, 2019.
• Differential Privacy of Hierarchical Census Data: An Optimization Approach, Fernandino Fioretto and Pascal Van Hentenryck. n Proceedings of the International Conference on Principles and Practice of Constraint Programming (CP), 2019.

Check our recent paper on comparing machine learning and logic models. Fascinating area.

 

Our paper on Assortment Optimization in Sequential Multinomial Logit is online. The framework captures the situation where products are partitioned into two levels, to capture differences in attractiveness, brand awareness and, or visibility in the market. When a consumer is presented with an assortment of products, she first considers products in the first level and, if none of them is purchased, products in the second level are considered. This model is a special case of the Perception-Adjusted Luce Model (PALM) recently proposed recently by Echenique et al. The problem for three or more levels is open … for those interested in a challenge.

Check the minicp website for the 1.0 release. MiniCP is a lightweight, open-source solver for constraint programming. It is motivated by educational purposes and, in particular, the desire to provide the core implementation of a constraint-programming solver for students in computer science and industrial engineering. The design of MiniCP provides a one-to-one mapping between the theoretical and implementation concepts and its compositional abstractions favor extensibility and flexibility. MiniCP obviously does not support all available constraint-programming features and implementation techniques, but these could be implemented as future extensions or exploratory projects. MiniCP also comes with a full set of exercises, unit tests, and development projects.