Robust Optimization

Context-Aware Cluster-Based Multi-Uncertainty-Set Distributionally Robust Chance-Constrained DC Optimal Power Flow

  • Qiao Yi Wang
  • Wei Liu
  • Bo Yu
    • Categories Applications - Science and Engineering, Energy, Robust Optimization Tags , , , , ,

    This paper proposes a context-aware multi-uncertainty-set distributionally robust chance-constrained DC optimal power flow model. Meteorological features are projected to partition the non-convex error support into a context-dependent decomposition of conditional local ambiguity sets, with conditional weights inferred via kernel regression. The minimax problem is reformulated into a finite-dimensional second-order cone program with proven asymptotic consistency. … Read more

    Stochastic set-valued optimization and its application to robust learning

  • Tommaso Giovannelli
  • Jingfu Tan
  • Luis Nunes Vicente
    • Categories Robust Optimization Tags , , ,

    In this paper, we develop a stochastic set-valued optimization (SVO) framework tailored for robust machine learning. In the SVO setting, each decision variable is mapped to a set of objective values, and optimality is defined via set relations. We focus on SVO problems with hyperbox sets, which can be reformulated as multi-objective optimization (MOO) problems … Read more

    Branch-and-Cut for Mixed-Integer Linear Decision-Dependent Robust Optimization

  • Henri Lefebvre
  • Martin Schmidt
  • Simon Stevens
  • Johannes Thürauf
    • Categories Bilevel Optimization, Branch and Cut Algorithms, Robust Optimization Tags , , , , ,

    Decision-dependent robust optimization (DDRO) problems are usually tackled by reformulating them using a strong-duality theorem for the uncertainty set model. If the uncertainty set is, however, described by a mixed-integer linear model, dualization techniques cannot be applied and the literature on solution methods is very scarce. In this paper, we exploit the equivalence of DDRO … Read more

    Risk-Averse Stochastic User Equilibrium on Uncertain Transportation Networks

  • Wencheng Bao
  • Chrysafis Vogiatzis
  • Eleftheria Kontou
    • Categories Network Optimization, Robust Optimization, Transportation Tags , , , , ,

    Extreme weather events, like flooding, disrupt urban transportation networks by reducing speeds and capacities, and by closing roadways. These hazards create regime-dependent uncertainty in link performance and travel-time distribution tails, challenging conventional traffic assignment that relies on the expectation of cost or mean excess of cost summation. This study develops a risk- and ambiguity-aware traffic … Read more

    Robust Admission Via Two-Stage Stable Matching Under Ranking Uncertainty

  • Gustavo Angulo
    • Categories Game Theory, Integer Programming, Robust Optimization Tags , , ,

    We study a two-stage admission and assignment problem under uncertainty arising in university admission systems. In the first stage, applicants are admitted to an initial two-year program. In the second stage, admitted applicants are assigned to degree programs through an articulation mechanism subject to capacity constraints. Uncertainty stems from the academic performance of admitted applicants … Read more

    Exact and Heuristic Methods for Gamma-Robust Min-Max Problems

  • Yasmine Beck
    • Categories Bilevel Optimization, Combinatorial Optimization, Robust Optimization Tags , , , ,

    Bilevel optimization is a powerful tool for modeling hierarchical decision-making processes, which arise in various real-world applications. Due to their nested structure, however, bilevel problems are intrinsically hard to solve—even if all variables are continuous and all parameters of the problem are exactly known. Further challenges arise if mixed-integer aspects and problems under uncertainty are … Read more

    Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach

  • Jie Wang
    • Categories Optimization in Data Science, Robust Optimization, Stochastic Programming Tags ,

    In this paper, we introduce a framework for contextual distributionally robust optimization (DRO) that considers the causal and continuous structure of the underlying distribution by developing interpretable and tractable decision rules that prescribe decisions using covariates. We first introduce the causal Sinkhorn discrepancy (CSD), an entropy-regularized causal Wasserstein distance that encourages continuous transport plans while … Read more

    A single loop method for quadratic minmax optimization

  • Stefano Cipolla
  • Oliver Stein
  • Alain Zemkoho
    • Categories Linear Programming, Quadratic Programming, Robust Optimization Tags

    We consider a quadratic minmax problem with coupled inner constraints and propose a method to compute a class of stationary points. To motivate the need to compute such stationary points, we first show that they are meaningful, in the sense that they can be locally optimal for our problem under suitable linear independence and second-order … Read more

    A Gauge Set Framework for Flexible Robustness Design

  • Ningji Wei
  • Xian Yu
  • Peter Yun Zhang
    • Categories Robust Optimization, Stochastic Programming

    This paper proposes a unified framework for designing robustness in optimization under uncertainty using gauge sets, convex sets that generalize distance and capture how distributions may deviate from a nominal reference. Representing robustness through a gauge set reweighting formulation brings many classical robustness paradigms under a single convex-analytic perspective. The corresponding dual problem, the upper … Read more