semi-infinite programming

Optimality-Based 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 optimality-based discretization (cutting-plane) methods for the global optimization of nonconvex semi-infinite programs (SIPs). We begin by formulating the optimal 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 efficient method for solving these max-min … 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

    On approximate solutions for robust semi-infinite multi-objective convex symmetric cone optimization

  • Baha Alzalg
  • Amira Achouak Oulha
    • Categories Linear, Cone and Semidefinite Programming, Robust Optimization, Semi-infinite Programming Tags , , , ,

    We present approximate solutions for the robust semi-infinite multi-objective convex symmetric cone programming problem. By using the robust optimization approach, we establish an approximate optimality theorem and approximate duality theorems for approximate solutions in convex symmetric cone optimization problem involving infinitely many constraints to be satisfied and multiple objectives to be optimized simultaneously under the … Read more

    Adaptive discretization-based algorithms for semi-infinite programs with unbounded variables

  • Daniel Jungen
  • Hatim Djelassi
  • Alexander Mitsos
    • Categories Global Optimization Tags , ,

    The proof of convergence of adaptive discretization-based algorithms for semi-infinite programs (SIPs) usually relies on compact host sets for the upper- and lower-level variables. This assumption is violated in some applications, and we show that indeed convergence problems can arise when discretization-based algorithms are applied to SIPs with unbounded variables. To mitigate these convergence problems, … Read more

    Moreau envelope of supremum functions with applications to infinite and stochastic programming

  • Pedro Pérez-Aros
  • Emilio Vilches
    • Categories Convex Optimization, Nonsmooth Optimization, Stochastic Programming Tags , , , , ,

    In this paper, we investigate the Moreau envelope of the supremum of a family of convex, proper, and lower semicontinuous functions. Under mild assumptions, we prove that the Moreau envelope of a supremum is the supremum of Moreau envelopes, which allows us to approximate possibly nonsmooth supremum functions by smooth functions that are also the … Read more

    Volumetric barrier decomposition algorithms for two-stage stochastic linear semi-infinite programming

  • Lewa' Alzaleq
  • Baha Alzalg
  • Asma Gafour
    • Categories Linear Programming, Semi-infinite Programming, Stochastic Programming Tags , , , ,

    In this paper, we study the two-stage stochastic linear semi-infinite programming with recourse to handle uncertainty in data defining (deterministic) linear semi-infinite programming. We develop and analyze volumetric barrier decomposition-based interior point methods for solving this class of optimization problems, and present a complexity analysis of the proposed algorithms. We establish our convergence analysis by … Read more

    Decomposition Algorithms for Distributionally Robust Optimization using Wasserstein Metric

  • Fengqiao Luo
  • Sanjay Mehrotra
    • Categories Data-Mining, Robust Optimization, Semi-infinite Programming Tags , , , ,

    We study distributionally robust optimization (DRO) problems where the ambiguity set is de ned using the Wasserstein metric. We show that this class of DRO problems can be reformulated as semi-in nite programs. We give an exchange method to solve the reformulated problem for the general nonlinear model, and a central cutting-surface method for the convex case, … Read more

    Semi-infinite programming using high-degree polynomial interpolants and semidefinite programming

  • Dávid Papp
    • Categories Semi-definite Programming, Semi-infinite Programming, Statistics Tags , , , ,

    In a common formulation of semi-infinite programs, the infinite constraint set is a requirement that a function parametrized by the decision variables is nonnegative over an interval. If this function is sufficiently closely approximable by a polynomial or a rational function, then the semi-infinite program can be reformulated as an equivalent semidefinite program. Solving this … Read more

    A collision detection approach for maximizing the material utilization

  • Volker Maag
    • Categories Constrained Nonlinear Optimization, Semi-infinite Programming Tags , , , ,

    We introduce a new method for a task of maximal material utilization, which is is to fit a flexible, scalable three-dimensional body into another aiming for maximal volume whereas position and shape may vary. The difficulty arises from the containment constraint which is not easy to handle numerically. We use a collision detection method to … Read more

    A cutting surface algorithm for semi-infinite convex programming with an application to moment robust optimization

  • Sanjay Mehrotra
  • Dávid Papp
    • Categories Robust Optimization, Semi-infinite Programming, Stochastic Programming Tags , , , , , , ,

    We first present and analyze a central cutting surface algorithm for general semi-infinite convex optimization problems, and use it to develop an algorithm for distributionally robust optimization problems in which the uncertainty set consists of probability distributions with given bounds on their moments. The cutting surface algorithm is also applicable to problems with non-differentiable semi-infinite … Read more