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.
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. Dan's research focuses on fundamental methodological and computational aspects of optimization, with an emphasis on very large-scale, non-convex and discrete optimization 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 solutions 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.