authornorthwesterndrooptimization

Hamed Rahimian

Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208. Email: hamed.rahimian@northwestern.edu.

Hamed Rahimian is an optimization researcher in the IEMS department at Northwestern University, working on distributionally robust optimization (DRO) and its computational methods. He is the first author (with Sanjay Mehrotra) of the comprehensive 2022 survey Distributionally Robust Optimization: A Review, the most-cited single reference for the operations-research treatment of DRO.

Key contributions

  • 2019 / 2022 — DRO survey (with Mehrotra). The 90+ page Open Journal of Mathematical Optimization review that organises the DRO literature into four optimisation paradigms (SO, RO, CCO, risk-averse) and four ambiguity-set families (discrepancy, moment, shape, kernel). This wiki's main DRO page is structured around this paper's taxonomy.
  • 2019 — Effective / ineffective scenarios in DRO. With Mehrotra, defined the notion of "effective" scenarios in a Wasserstein-DRO problem with finite sample space — scenarios whose probability is forced to zero in the worst case. Identifies a small set of "active" scenarios for computational speedup.
  • 2019 — Continuous-sample-space newsvendor DRO. Extension of the effective-scenario work to a continuous support; closed-form optimal solution and identification of maximal effective subsets of demand.
  • Cutting-surface / exchange methods for DRO. Co-author of one of the principal algorithms for solving semi-infinite DRO problems.

Why this matters for the wiki

Rahimian's survey is the single best entry point for the theoretical basis of any DRO-based risk model. The wiki uses it as the primary reference for the DRO concept, Wasserstein ambiguity set, coherent risk measures, and robust optimization pages.

See also