Dan Iancu and Nikos Trichakis
The paper by D. Iancu and N. Trichakis "Pareto Efficiency in Robust Optimization” fundamentally improves the understanding of robust optimization (RO). Specifically, the authors convincingly demonstrate that by focusing exclusively on worst-case outcomes, the classical RO paradigm can lead to inefficiencies and sub-optimal performance in practice. They extend the RO framework and propose methods that can verify Pareto optimality and generate Pareto robustly optimal solutions using the same computation effort as is required for solving the classical RO problem. The paper shows that Pareto robustly optimal solutions have a significant upside, at no extra cost or downside. As a result the paper is likely to have a profound influence on the the entire field of robust optimization.
Katya Scheinberg (chair), Yongpei Guan, Fatma Kilinc-Karzan, Andrea Lodi