Month: August 2020

On the Impact of Deep Learning-based Time-series Forecasts on Multistage Stochastic Programming Policies

  • Merve Bodur
  • Mucahit Cevik
  • Juyoung Wang
    • Categories Stochastic Programming Tags , , , ,

    Multistage stochastic programming provides a modeling framework for sequential decision-making problems that involve uncertainty. One typically overlooked aspect of this methodology is how uncertainty is incorporated into modeling. Traditionally, statistical forecasting techniques with simple forms, e.g., (first-order) autoregressive time-series models, are used to extract scenarios to be added to optimization models to represent the uncertain … Read more

    A Learning Based Algorithm for Drone Routing

  • Umut Ermağan
  • Barış Yıldız
  • Sibel Salman
    • Categories Applications - OR and Management Sciences Tags , , ,

    We introduce a learning based algorithm to solve the drone routing problem with recharging stops that arises in many applications such as precision agriculture, search and rescue and military surveillance. The heuristic algorithm, namely Learn and Fly (L\&F), learns from the features of high quality solutions to optimize recharging visits, starting from a given Hamiltonian … Read more

    Complexity Aspects of Fundamental Questions in Polynomial Optimization

  • Jeffrey Zhang
    • Categories Game Theory, Global Optimization Theory, Nonlinear Optimization Tags , , , ,

    In this thesis, we settle the computational complexity of some fundamental questions in polynomial optimization. These include the questions of (i) finding a local minimum, (ii) testing local minimality of a candidate point, and (iii) deciding attainment of the optimal value. Our results characterize the complexity of these three questions for all degrees of the … Read more

    A Two-level ADMM Algorithm for AC OPF with Convergence Guarantees

  • Xu Andy Sun
  • Kaizhao Sun
    • Categories Constrained Nonlinear Optimization, Network Optimization, Parallel Algorithms Tags , , ,

    This paper proposes a two-level distributed algorithmic framework for solving the AC optimal power flow (OPF) problem with convergence guarantees. The presence of highly nonconvex constraints in OPF poses significant challenges to distributed algorithms based on the alternating direction method of multipliers (ADMM). In particular, convergence is not provably guaranteed for nonconvex network optimization problems … Read more

    Conference scheduling: a clustering-based approach

  • Teobaldo Bulhões
  • Anand Subramanian
  • Rubens Correia
    • Categories Integer Programming, Scheduling Tags , ,

    Scheduling the technical sessions of scientific events is an arduous task commonly faced by many organizers worldwide. Due the particularities of each conference, there is no consensus regarding the problem definition, and researchers have tackled each specific case individually. Despite their distinct characteristics, one often expects the sessions to be composed of presentations of similar … Read more

    Routing and Wavelength Assignment with Protection: A Quadratic Unconstrained Binary Optimization Approach

  • Merve Bodur
  • Hamed Pouya
  • Oylum Seker
    • Categories 0-1 Programming, Quadratic Programming, Telecommunications

    The routing and wavelength assignment with protection is an important problem in telecommunications. Given an optical network and incoming connection requests, a commonly studied variant of the problem aims to grant maximum number of requests by assigning lightpaths at minimum network resource usage level, while ensuring the provided services remain functional in case of a … Read more

    The Strip Method for Shape Derivatives

  • Harbir Antil
  • Drew P. Kouri
  • Sean Hardesty
  • Denis Ridzal
    • Categories Infinite Dimensional Optimization, Multidisciplinary Design Optimization, Optimization of Systems modeled by PDEs Tags , , , ,

    A major challenge in shape optimization is the coupling of finite element method (FEM) codes in a way that facilitates efficient computation of shape derivatives. This is particularly difficult with multiphysics problems involving legacy codes, where the costs of implementing and maintaining shape derivative capabilities are prohibitive. The volume and boundary methods are two approaches … Read more

    On scaled stopping criteria for a safeguarded augmented Lagrangian method with theoretical guarantees

  • Roberto Andreani
  • Gabriel Haeser
  • Paulo J. S. Silva
  • María Laura Schuverdt
  • Leonardo D. Secchin
    • Categories Nonlinear Optimization Tags , , ,

    This paper discusses the use of a stopping criterion based on the scaling of the Karush-Kuhn-Tucker (KKT) conditions by the norm of the approximate Lagrange multiplier in the ALGENCAN implementation of a safeguarded augmented Lagrangian method. Such stopping criterion is already used in several nonlinear programming solvers, but it has not yet been considered in … Read more

    Multistage stochastic programs with the entropic risk measure

  • Oscar Dowson
  • David P. Morton
  • Bernardo K. Pagnoncelli
    • Categories Stochastic Programming

    Over the last two decades, coherent risk measures have been well studied as a principled, axiomatic way to measure the risk of a random variable. Because of this axiomatic approach, coherent risk measures have a number of attractive features for computation, and they have been integrated into a variety of stochastic programming algorithms, including stochastic … Read more

    A unifying framework for the analysis of projection-free first-order methods under a sufficient slope condition

  • Francesco Rinaldi
  • Damiano Zeffiro
    • Categories Nonlinear Optimization Tags , , , ,

    The analysis of projection-free first order methods is often complicated by the presence of different kinds of “good” and “bad” steps. In this article, we propose a unifying framework for projection-free methods, aiming to simplify the converge analysis by getting rid of such a distinction between steps. The main tool employed in our framework is … Read more