Applications – Science and Engineering

Using an Analytical Computational-Geometry Library to Model Nonoverlap and Boundary-Distance Constraints and their Application to Packing Poly-Bézier Shapes

  • Paul Morton
    • Categories Applications - Science and Engineering, Bound-constrained Optimization, Optimization Software and Modeling Systems Tags , , , , , , , , , , ,

    In this paper we will show how to model nonoverlap as well as uniform and nonuniform boundary-distance constraints between poly-Bézier shapes using an analytical computational-geometry library. We then use this capability to develop, implement and analyze analytical-optimization solutions to minimum-area rectangular-boundary packing-problems as well as minimum-area one- and two-dimensional puzzle-piece packing-problems. In the process, we … Read more

    New interior-point approach for one- and two-class linear support vector machines using multiple variable splitting

  • Jordi Castro
    • Categories Data-Mining, Linear, Cone and Semidefinite Programming Tags , , , ,

    Multiple variable splitting is a general technique for decomposing problems by using copies of variables and additional linking constraints that equate their values. The resulting large optimization problem can be solved with a specialized interior-point method that exploits the problem structure and computes the Newton direction with a combination of direct and iterative solvers (i.e., … Read more

    Convergence Analysis of Block Majorize-Minimize Subspace Approaches

  • Jean-Baptiste Fest
  • Émilie Chouzenoux
    • Categories Applications - Science and Engineering, Unconstrained Optimization Tags , , ,

    Majorization-Minimization (MM) consists of a class of efficient and effective optimization algorithms that benefit from solid theoretical foundations. MM methods have shown their great ability to tackle efficiently challenging optimization problems from signal processing, image processing, inverse problems and machine learning. When processing large amount of data/variable, as it may happen in 3D image processing, … Read more

    Analysis non-sparse recovery for non-convex relaxed $\ell_q$ minimization

  • Jianwen Huang
  • Feng Zhang
  • Xinling Liu
  • Jianjun Wang
    • Categories Data-Mining, Nonsmooth Optimization, Unconstrained Optimization Tags , , , ,

    This paper studies construction of signals, which are sparse or nearly sparse with respect to a tight frame $D$ from underdetermined linear systems. In the paper, we propose a non-convex relaxed $\ell_q(0 Article Download View Analysis non-sparse recovery for non-convex relaxed $ell_q$ minimization

    Reaching Paris Agreement Goal through CDR/DAC Development: a Compact OR Model

  • Frédéric Babonneau
  • Alain Haurie
  • Alain Vielle
    • Categories Civil and Environmental Engineering Tags , , , ,

    A compact operations research (OR) model is proposed to analyse the prospects of meeting the Paris Agreement targets when direct air capture technologies can be used or not. The main features of the model are (i) the representation of the economy and energy use with a nested constant elasticity of substitution production function; (ii) the … Read more

    Modeling Design and Control Problems Involving Neural Network Surrogates

  • Dominic Yang
  • Prasanna Balaprakash
  • Sven Leyffer
    • Categories (Mixed) Integer Nonlinear Programming, Control Applications, Nonsmooth Optimization Tags , , , ,

    We consider nonlinear optimization problems that involve surrogate models represented by neural net-works. We demonstrate first how to directly embed neural network evaluation into optimization models, highlight a difficulty with this approach that can prevent convergence, and then characterize stationarity of such models. We then present two alternative formulations of these problems in the specific … Read more

    Stochastic Dual Dynamic Programming for Optimal Power Flow Problems under Uncertainty

  • Adriana Kiszka
  • David Wozabal
    • Categories Energy, Semi-definite Programming, Stochastic Programming Tags , , ,

    We propose the first computationally tractable framework to solve multi-stage stochastic optimal power flow (OPF) problems in alternating current (AC) power systems. To this end, we use recent results on dual convex semi-definite programming (SDP) relaxations of OPF problems in order to adapt the stochastic dual dynamic programming (SDDP) algorithm for problems with a Markovian … Read more

    On the Fairness of Aggregator’s Incentives in Residential Demand Response

  • Michael David de Souza Dutra
  • Natalia Alguacil Conde
    • Categories Energy, Integer Programming Tags , , , , ,

    The main motivation of this work is to provide an optimization-based tool for an aggregator involved in residential demand response (DR) programs. The proposed tool comply with the following requirements, which are widely accepted by the residential DR literature: (i) the aggregated consumption should be optimized under a particular utility’s target, such as the minimization … Read more

    Mixed-Integer Optimization with Constraint Learning

  • Donato Maragno
  • Holly Wiberg
  • Dimitris Bertsimas
  • Ş. İlker Birbil
  • Dick den Hertog
  • Adejuyigbe Fajemisin
    • Categories (Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Data-Mining Tags , , ,

    We establish a broad methodological foundation for mixed-integer optimization with learned constraints. We propose an end-to-end pipeline for data-driven decision making in which constraints and objectives are directly learned from data using machine learning, and the trained models are embedded in an optimization formulation. We exploit the mixed-integer optimization-representability of many machine learning methods, including … Read more

    Exact and Heuristic Solution Techniques for Mixed-Integer Quantile Minimization Problems

  • Diego Cattaruzza
  • Martine Labbé
  • Matteo Petris
  • Marius Roland
  • Martin Schmidt
    • Categories (Mixed) Integer Linear Programming, Applications - Science and Engineering, Stochastic Programming Tags , , , ,

    We consider mixed-integer linear quantile minimization problems that yield large-scale problems that are very hard to solve for real-world instances. We motivate the study of this problem class by two important real-world problems: a maintenance planning problem for electricity networks and a quantile-based variant of the classic portfolio optimization problem. For these problems, we develop … Read more