Nonlinear Optimization

A Collection of 1,300 Dynamical Systems for Testing Data Fitting, Optimal Control, Experimental Design, Identification, Simulation or Similar Software – User’s Guide

  • Klaus Schittkowski
    • Categories Modeling Languages and Systems, Optimization Software Benchmark, Systems governed by Differential Equations Optimization

    We describe a collection of test problems which have been used to develop and test data fitting software for identifying parameters in explicit model functions, dynamical systems of equations, Laplace transformations, systems of ordinary differential equations, differential algebraic equations, or systems of one-dimensional time-dependent partial differential equations with or without algebraic equations. The test cases … Read more

    MathOptimizer: A nonlinear optimization package for Mathematica users

  • Frank J. Kampas
  • János Pintér
    • Categories Constrained Nonlinear Optimization, Global Optimization, Optimization Software and Modeling Systems

    Mathematica is an advanced software system that enables symbolic computing, numerics, program code development, model visualization and professional documentation in a unified framework. Our MathOptimizer software package serves to solve global and local optimization models developed using Mathematica. We introduce MathOptimizer’s key features and discuss its usage options that support a range of operational modes. … Read more

    Alternating direction algorithms for total variation deconvolution in image reconstruction

  • Tao Min
  • Junfeng Yang
    • Categories Convex Optimization, Nonsmooth Optimization, Unconstrained Optimization Tags , , , ,

    Image restoration and reconstruction from blurry and noisy observation is known to be ill-posed. To stabilize the recovery, total variation (TV) regularization was introduced by Rudin, Osher and Fatemi in \cite{LIR92}, which has demonstrated superiority in preserving image edges. However, the nondifferentiability of TV makes the underlying optimization problems difficult to solve. In this paper, … Read more

    An Updated Set of 306 Test Problems for Nonlinear Programming with Validated Optimal Solutions

  • Klaus Schittkowski
    • Categories Constrained Nonlinear Optimization, Optimization Software Benchmark

    The availability of nonlinear programming test problems is extremely important to test optimization codes or to develop new algorithms. We describe the usage of the Fortran subroutines for all 306 test problems of two previous collections of the author, see Hock and Schittkowski (1981) and Schittkowski (1987). For each test example, we provide an optimal … Read more

    Data Fitting and Experimental Design in Dynamical Systems with EASY-FIT ModelDesign

  • Klaus Schittkowski
    • Categories Nonlinear Systems and Least-Squares, Problem Solving Environments, Systems governed by Differential Equations Optimization

    EASY-FIT is an interactive software system to identify parameters and compute optimal designs in explicit model functions, steady-state systems, Laplace transformations, systems of ordinary differential equations, differential algebraic equations, or systems of one-dimensional time dependent partial differential equations with or without algebraic equations. Proceeding from given experimental data, i.e. observation times and measurements, the minimum … Read more

    A new sequential optimality condition for constrained optimization and algorithmic consequences

  • Roberto Andreani
  • José Mario Martínez
  • Benar Fux Svaiter
    • Categories Nonlinear Optimization Tags , , ,

    Necessary first-order sequential optimality conditions provide adequate theoretical tools to justify stopping criteria for nonlinear programming solvers. These conditions are satisfied by local minimizers of optimization problems independently of the fulfillment of constraint qual- i cations. A new strong sequential optimality condition is introduced in the present paper. A proof that a well established Augmented Lagrangian … Read more

    An L1 Elastic Interior-Point Method for Mathematical Programs with Complementarity Constraints

  • Zoumana Coulibaly
  • Dominique Orban
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization Tags , , , , , , ,

    We propose an interior-point algorithm based on an elastic formulation of the L1-penalty merit function for mathematical programs with complementarity constraints. The method generalizes that of Gould, Orban and Toint (2003) and naturally converges to a strongly stationary point or delivers a certificate of degeneracy without recourse to second-order intermediate solutions. Remarkably, the method allows … Read more

    A Factorization with Update Procedures for a KKT Matrix Arising in Direct Optimal Control

  • Hans Georg Bock
  • Christian Kirches
  • Sebastian Sager
  • Johannes P. Schlöder
    • Categories Quadratic Programming, Systems governed by Differential Equations Optimization Tags , ,

    Quadratic programs obtained for optimal control problems of dynamic or discrete–time processes usually involve highly block structured Hessian and constraints matrices. Efficient numerical methods for the solution of such QPs have to respect and exploit this block structure. In interior point methods, this is elegantly achieved by the widespread availability of advanced sparse symmetric indefinite … Read more

    PARNES: A rapidly convergent algorithm for accurate recovery of sparse and approximately sparse signals

  • Ming Gu
  • Lek-Heng Lim
  • Cinna Julie Wu
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Optimization Software Benchmark Tags , , , , , , ,

    In this article we propose an algorithm, NESTA-LASSO, for the LASSO problem (i.e., an underdetermined linear least-squares problem with a one-norm constraint on the solution) that exhibits linear convergence under the restricted isometry property (RIP) and some other reasonable assumptions. Inspired by the state-of-the-art sparse recovery method, NESTA, we rely on an accelerated proximal gradient … Read more

    Second-Order Cone Relaxations for Binary Quadratic Polynomial Programs

  • Miguel F. Anjos
  • Bissan Ghaddar
  • Juan C. Vera
    • Categories Combinatorial Optimization, Linear, Cone and Semidefinite Programming, Nonlinear Optimization Tags , , ,

    Several types of relaxations for binary quadratic polynomial programs can be obtained using linear, second-order cone, or semidefinite techniques. In this paper, we propose a general framework to construct conic relaxations for binary quadratic polynomial programs based on polynomial programming. Using our framework, we re-derive previous relaxation schemes and provide new ones. In particular, we … Read more