Robust Optimization

Integer Programming Approaches for Distributionally Robust Chance Constraints with Adjustable Risks

  • Yiling Zhang
    • Categories Integer Programming, Robust Optimization, Stochastic Programming

    We study distributionally robust chance constrained programs (DRCCPs)  with individual chance constraints and random right-hand sides. The DRCCPs treat the risk tolerances associated with the distributionally robust chance constraints (DRCCs) as decision variables to trade off between the system cost and risk of violations by penalizing the risk tolerances in the objective function. We consider … Read more

    Robust Workforce Management with Crowdsourced Delivery

  • Chun Cheng
  • Melvyn Sim
  • Yue Zhao
    • Categories Robust Optimization, Transportation Tags , , ,

    We investigate how crowdsourced delivery platforms with both contracted and ad-hoc couriers can effectively manage their workforce to meet delivery demands amidst uncertainties. Our objective is to minimize the hiring costs of contracted couriers and the crowdsourcing costs of ad-hoc couriers while considering the uncertain availability and behavior of the latter. Due to the complication … Read more

    Robust Two-Dose Vaccination Schemes and the Directed b-Matching Problem

  • Jenny Segschneider
  • Arie M.C.A. Koster
    • Categories Applications - OR and Management Sciences, Robust Optimization Tags , , , ,

    In light of the recent pandemic and the shortage of vaccinations during their roll-out, questions arose regarding the best strategy to achieve immunity throughout the population by adjusting the time gap between the two necessary vaccination doses. This strategy has already been studied from different angles by various researches. However, the deliveries of vaccination doses … Read more

    Robust two-stage combinatorial optimization problems under discrete demand uncertainties and consistent selection constraints

  • SabrinaSchmitz
  • Christina Büsing
    • Categories Robust Optimization Tags , , , ,

    In this paper, we study a robust two-stage concept of combinatorial optimization problems under discrete demand uncertainty. Combinatorial optimization problems are based on a finite set of elements for which we decide whether they are part of a solution. We divide the elements into two types, the so-called fixed and free elements. In a first … Read more

    Approximation Guarantees for Min-max-min Robust Optimization and K-Adaptability under Objective Uncertainty

  • Jannis Kurtz
    • Categories Approximation Algorithms, Robust Optimization Tags , ,

    In this work we investigate the min-max-min robust optimization problem for binary problems with uncertain cost-vectors. The idea of the approach is to calculate a set of k feasible solutions which are worst-case optimal if in each possible scenario the best of the k solutions is implemented. It is known that the min-max-min robust problem … Read more

    Two-stage and Lagrangian Dual Decision Rules for Multistage Adaptive Robust Optimization

  • Maryam Daryalal
  • Ayse Nur Arslan
  • Merve Bodur
    • Categories Robust Optimization, Stochastic Programming Tags , ,

    In this work, we design primal and dual bounding methods for multistage adaptive robust optimization (MSARO) problems by adapting two decision rules rooted in the stochastic programming literature. This approach approximates the primal and dual formulations of an MSARO problem with two-stage models. From the primal perspective, this is achieved by applying two-stage decision rules … Read more

    A first-order augmented Lagrangian method for constrained minimax optimization

  • Zhaosong Lu
  • Sanyou Mei
    • Categories Constrained Nonlinear Optimization, Robust Optimization Tags , , ,

    \(\) In this paper we study a class of constrained minimax problems. In particular, we propose a first-order augmented Lagrangian method for solving them, whose subproblems turn out to be a much simpler structured minimax problem and are suitably solved by a first-order method recently developed in [26] by the authors. Under some suitable assumptions, … Read more

    Data-driven Prediction of Relevant Scenarios for Robust Combinatorial Optimization

  • Marc Goerigk
  • Jannis Kurtz
    • Categories Optimization in Data Science, Robust Optimization Tags , , ,

    We study iterative methods for (two-stage) robust combinatorial optimization problems with discrete uncertainty. We propose a machine-learning-based heuristic to determine starting scenarios that provide strong lower bounds. To this end, we design dimension-independent features and train a Random Forest Classifier on small-dimensional instances. Experiments show that our method improves the solution process for larger instances … Read more

    A Robust Location-Allocation Model for Optimizing a Multi-Echelon Blood Supply Chain Network Under Uncertainty

  • Masoud Asadpour Ahmadchali
  • Mahdi Ebrahimzadeh Afrouzi
    • Categories Robust Optimization, Supply Chain Management Tags , , , , ,

    Designing and planning blood supply chains is very complicated due to its uncertain nature, such as uncertain blood demand, high vulnerability to disruptions, irregular donation, and blood perishability. In this vein, this paper seeks to optimize a multi-echelon blood supply chain network under uncertainty by designing a robust location-allocation model. The magnitude of the earthquake … Read more

    Set-based Robust Optimization of Uncertain Multiobjective Problems via Epigraphical Reformulations

  • Gabriele Eichfelder
  • Ernest Quintana
    • Categories Multi-Criteria Optimization, Robust Optimization Tags , , ,

    In this paper, we study a method for finding robust solutions to multiobjective optimization problems under uncertainty. We follow the set-based minmax approach for handling the uncertainties which leads to a certain set optimization problem with the strict upper type set relation. We introduce, under some assumptions, a reformulation using instead the strict lower type … Read more