robust optimization

Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs

  • Evren Turan
  • Johannes Jäschke
  • Rohit Kannan
    • Categories Global Optimization, Semi-infinite Programming Tags , , , , ,

    We use sensitivity analysis to design bounding-focused discretization (cutting-surface) methods for the global optimization of nonconvex semi-infinite programs (SIPs). We begin by formulating the optimal bounding-focused discretization of SIPs as a max-min problem and propose variants that are more computationally tractable. We then use parametric sensitivity theory to design an effective heuristic approach for solving … 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

    Approximation Algorithms 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 and the k-adaptability robust optimization problem for binary problems with uncertain costs. The idea of the first 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 … 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 motivated by two decision rules rooted in the stochastic programming literature. From the primal perspective, this is achieved by applying decision rules that restrict the functional forms of only a certain subset of decision variables resulting in an … 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

    A Brief Introduction to Robust Bilevel Optimization

  • Yasmine Beck
  • Ivana Ljubić
  • Martin Schmidt
    • Categories Robust Optimization Tags , ,

    Bilevel optimization is a powerful tool for modeling hierarchical decision making processes. However, the resulting problems are challenging to solve – both in theory and practice. Fortunately, there have been significant algorithmic advances in the field so that we can solve much larger and also more complicated problems today compared to what was possible to … Read more

    General Polyhedral Approximation of Two-Stage Robust Linear Programming

  • LukasGrunau
  • Tim Niemann
  • Sebastian Stiller
    • Categories Approximation Algorithms, Combinatorial Optimization, Robust Optimization Tags , , , ,

    We consider two-stage robust linear programs with uncertain righthand side. We develop a General Polyhedral Approximation (GPA), in which the uncertainty set $\mathcal{U}$ is substituted by a finite set of polytopes derived from the vertex set of an arbitrary polytope that dominates $\mathcal{U}$. The union of the polytopes need not contain $\mathcal{U}$. We analyse and … Read more

    On the Relation Between Affinely Adjustable Robust Linear Complementarity and Mixed-Integer Linear Feasibility Problems

  • Christian Biefel
  • Martin Schmidt
    • Categories (Mixed) Integer Linear Programming, Complementarity and Variational Inequalities Tags , , ,

    We consider adjustable robust linear complementarity problems and extend the results of Biefel et al.~(2022) towards convex and compact uncertainty sets. Moreover, for the case of polyhedral uncertainty sets, we prove that computing an adjustable robust solution of a given linear complementarity problem is equivalent to solving a properly chosen mixed-integer linear feasibility problem. ArticleDownload … Read more

    Target-Oriented Regret Minimization for Satisficing Monopolists

  • Napat Rujeerapaiboon
  • Yize Wei
  • Yilin Xue
    • Categories Applications - OR and Management Sciences, Finance and Economics, Robust Optimization Tags , , , ,

    We study a robust monopoly pricing problem where a seller aspires to sell an item to a buyer. We assume that the seller, unaware of the buyer’s willingness to pay, ambitiously optimizes over a space of all individual rational and incentive compatible mechanisms with a regret-type objective criterion. Using robust optimization, Kocyigit et al. (2021) … Read more

    Robust Contextual Portfolio Optimization with Gaussian Mixture Models

  • Yijie Wang
  • Ling Dai
  • Grani A. Hanasusanto
  • Chin Pang Ho
    • Categories Finance and Economics, Robust Optimization Tags , ,

    We consider the portfolio optimization problem with contextual information that is available to better quantify and predict the uncertain returns of assets. Motivated by the regime modeling techniques for the finance market, we consider the setting where both the uncertain returns and the contextual information follow a Gaussian Mixture (GM) distribution. This problem is shown … Read more