EE, IEOR and APAM Professor Daniel Bienstock received the 2022 Khachiyan Prize for his fundamental methodological and computational contributions to optimization, with an emphasis on very large-scale, non-convex and discrete optimization problems.
The Khachiyan Prize of the INFORMS Optimization Society was established in 2010 and is awarded annually at the fall INFORMS Annual Meeting to an individual or a team for life-time achievements in the area of optimization. The award recognizes a sustained career of scholarship from nominees who are still active at the year of the nomination. The prize serves as an esteemed recognition of innovativeness and impact in the area of optimization, including theory and applications. Recipients of the INFORMS John von Neumann Theory Prize or the MPS/SIAM Dantzig Prize in prior years are not eligible for the Khachiyan Prize.
Citation: Daniel Bienstock is a unique scholar who blends deep mathematics with elegant computational implementation. To obtain practical solutions to large-scale optimization problems, one needs to leverage problem structure to design methodologically sound strategies, and then implement them in a computationally efficient manner - the trade-off between methodology and implementation has to be carefully calibrated for the effort to succeed. Dan has demonstrated this ability many times in his research career, over a wide range of such problems. He is very broad, prolific, and his research is unique in emphasizing both deep mathematics and efficient practical implementations. Seminal methodological contributions include fast approximate solution to very large, structured linear programs, and extended formulations for hard combinatorial integer programs. Dan’s work has also had a significant impact on several application areas, such as optimal development of open pit mines, and real time control of the power grid.