In conjunction with MISO and Vanderbilt University, the RAMC project will explore new approaches to market clearing and security-constrained optimal power flows. It will leverage techniques from stochastic optimization, machine learning, and risk management to improve the use of renewable energy in large-scale energy systems.
Author: Pascal Van Hentenryck
ISyE: Shaping the Future
Check the latest issue of the GT ISyE Magazine for all the exciting research and teaching activities at Georgia Tech.
Associate Chair for Innovation and Entrepreneurship
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.
Gas and Electricity Networks
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.
CSAI Distinguished Lecture in Nanjing University
2019 Seth Bonder Camp in Computational and Data Sciences
Check this article out for the wonderful Seth Bonder Camp we are teaching every year.
2019 ACP Doctoral Dissertation Award
My amazing student Eddie Lam will receive the 2019 ACP Doctoral Dissertation Award for his beautiful work at the intersection of Constraint Programming, Mathematical Programming, and Boolean Satisfiability, with applications in vehicle routing.
Differential Privacy
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.
Discrete Choice Models and Machine Learning
Check our recent paper on comparing machine learning and logic models. Fascinating area.
Assortment Optimization in Sequential Multinomial Logit
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.