Month: July 2022

A General Wasserstein Framework for Data-driven Distributionally Robust Optimization: Tractability and Applications

  • Jonathan Yu-Meng Li
  • Tiantian Mao
    • Categories Robust Optimization, Stochastic Programming Tags , ,

    Data-driven distributionally robust optimization is a recently emerging paradigm aimed at finding a solution that is driven by sample data but is protected against sampling errors. An increasingly popular approach, known as Wasserstein distributionally robust optimization (DRO), achieves this by applying the Wasserstein metric to construct a ball centred at the empirical distribution and finding … Read more

    A New Dual-Based Cutting Plane Algorithm for Nonlinear Adjustable Robust Optimization

  • Abbas Khademi
  • Ahmadreza Marandi
  • Majid Soleimani-damaneh
    • Categories Robust Optimization Tags , , , , ,

    This paper explores a class of nonlinear Adjustable Robust Optimization (ARO) problems, containing here-and-now and wait-and-see variables, with uncertainty in the objective function and constraints. By applying Fenchel’s duality on the wait-and-see variables, we obtain an equivalent dual reformulation, which is a nonlinear static robust optimization problem. Using the dual formulation, we provide conditions under … Read more

    Maximizing resilience in large-scale social networks

  • Samuel Kroger
  • Hamidreza Validi
  • Illya V. Hicks
    • Categories Combinatorial Optimization, Integer Programming, Network Optimization Tags , ,

    Motivated by the importance of social resilience as a crucial element in cascading leaving of users from a social network, we study identifying a largest relaxed variant of a degree-based cohesive subgraph: the maximum anchored k-core problem. Given graph G=(V,E) and integers k and b, the maximum anchored k-core problem seeks to find a largest … Read more

    Using Multiple Reference Vectors and Objective Scaling in the Feasibility Pump

  • Timo Berthold
  • Gioni Mexi
  • Domenico Salvagnin
    • Categories (Mixed) Integer Linear Programming, 0-1 Programming Tags ,

    The Feasibility Pump (FP) is one of the best-known primal heuristics for mixed-integer programming (MIP): more than 15 papers suggested various modifications of all of its steps. So far, no variant considered information across multiple iterations, but all instead maintained the principle to optimize towards a single reference integer point. In this paper, we evaluate … Read more

    A single cut proximal bundle method for stochastic convex composite optimization

  • Jiaming Liang
  • Vincent Guigues
  • Renato D.C. Monteiro
    • Categories Convex and Nonsmooth Optimization, Stochastic Programming Tags , , ,

    This paper considers optimization problems where the objective is the sum of a function given by an expectation and a closed convex composite function, and proposes stochastic composite proximal bundle (SCPB) methods for solving it. Complexity guarantees are established for them without requiring knowledge of parameters associated with the problem instance. Moreover, it is shown … Read more

    Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution

  • Jianhao Ma
  • Salar Fattahi
    • Categories Nonlinear Optimization, Statistics Tags , ,

    This work characterizes the effect of depth on the optimization landscape of linear regression, showing that, despite their nonconvexity, deeper models have more desirable optimization landscape. We consider a robust and over-parameterized setting, where a subset of measurements are grossly corrupted with noise and the true linear model is captured via an $N$-layer linear neural … Read more

    On optimally solving sub-tree scheduling for wireless sensor networks with partial coverage

  • Nicola Bianchessi
    • Categories Branch and Cut Algorithms, Network Optimization, Telecommunications Tags , , , , ,

    Energy efficiency and balancing are very important issues from the perspective of increasing the lifetime of a wireless sensor network (WSN). In this study, we concentrate on energy balancing. Given a WSN, we consider the problem to minimize its total power consumption over consecutive time slots with respect to communication activities. Disjoint subsets of nodes … Read more

    A Penalty Branch-and-Bound Method for Mixed-Integer Quadratic Bilevel Problems

  • Horländer Andreas
  • Martin Schmidt
    • Categories (Mixed) Integer Linear Programming, (Mixed) Integer Nonlinear Programming, Complementarity and Variational Inequalities Tags , , ,

    We propose an algorithm for solving bilevel problems with mixed-integer convex-quadratic upper level as well as convex-quadratic and continuous lower level. The method is based on a classic branch-and-bound procedure, where branching is performed on the integer constraints and on the complementarity constraints resulting from the KKT reformulation of the lower-level problem. However, instead of … Read more

    The superiorization method with restarted perturbations for split minimization problems with an application to radiotherapy treatment planning

  • Francisco J. Aragón Artacho
  • Yair Censor
  • Aviv Gibali
  • David Torregrosa-Belén
    • Categories Biomedical Applications, Constrained Nonlinear Optimization, Convex Optimization Tags , , , , , ,

    In this paper we study the split minimization problem that consists of two constrained minimization problems in two separate spaces that are connected via a linear operator that maps one space into the other. To handle the data of such a problem we develop a superiorization approach that can reach a feasible point with reduced … Read more