Nonlinear Optimization

On classes of set optimization problems which are reducible to vector optimization problems and its impact on numerical test instances

  • Gabriele Eichfelder
  • Tobias Gerlach
    • Categories Multi-Criteria Optimization, Nonlinear Optimization Tags , , , ,

    Set optimization with the set approach has recently gained increasing interest due to its practical relevance. In this problem class one studies optimization problems with a set-valued objective map and defines optimality based on a direct comparison of the images of the objective function, which are sets here. Meanwhile, in the literature a wide range … Read more

    Optimal linearized symmetric ADMM for separable convex programming

  • Jianchao Bai
  • Chang Xiaokai
  • Liu Sanyang
    • Categories Constrained Nonlinear Optimization

    Due to its wide applications and simple implementations, the Alternating Direction Method of Multipliers (ADMM) has been extensively investigated by researchers from different areas. In this paper, we focus on a linearized symmetric ADMM (LSADMM) for solving the multi- block separable convex minimization model. This LSADMM partitions the data into two group variables and updates … Read more

    Exact Semidefinite Formulations for a Class of (Random and Non-Random) Nonconvex Quadratic Programs

  • Samuel Burer
  • Yinyu Ye
    • Categories Global Optimization Theory, Quadratic Programming, Semi-definite Programming Tags , ,

    We study a class of quadratically constrained quadratic programs (QCQPs), called {\em diagonal QCQPs\/}, which contain no off-diagonal terms $x_j x_k$ for $j \ne k$, and we provide a sufficient condition on the problem data guaranteeing that the basic Shor semidefinite relaxation is exact. Our condition complements and refines those already present in the literature … Read more

    Combinatorial Integral Approximation for Mixed-Integer PDE-Constrained Optimization Problems

  • Mirko Hahn
  • Sebastian Sager
    • Categories (Mixed) Integer Nonlinear Programming, Optimization of Systems modeled by PDEs, Systems governed by Differential Equations Optimization Tags , , ,

    We apply the basic principles underlying combinatorial integral approximation methods for mixed-integer optimal control with ordinary differential equations in general, and the sum-up rounding algorithm specifically, to optimization problems with partial differential equation (PDE) constraints. By doing so, we identify two possible generalizations that are applicable to problems involving PDE constraints with mesh-dependent integer variables, … Read more

    FINITE ELEMENT MODEL UPDATING FOR STRUCTURAL APPLICATIONS

  • Maria Girardi
  • Margherita Porcelli
  • Cristina Padovani
  • Daniele Pellegrini
  • Leonardo Robol
    • Categories Civil and Environmental Engineering, Nonlinear Optimization Tags , , , ,

    A novel method for performing model updating on finite element models is presented. The approach is particularly tailored to modal analyses of buildings, by which the lowest frequencies, obtained by using sensors and system identification approaches, need to be matched to the numerical ones predicted by the model. This is done by optimizing some unknown … Read more

    Regional Complexity Analysis of Algorithms for Nonconvex Smooth Optimization

  • Frank E. Curtis
  • Daniel P. Robinson
    • Categories Nonlinear Optimization, Unconstrained Optimization Tags , , , , ,

    A strategy is proposed for characterizing the worst-case performance of algorithms for solving nonconvex smooth optimization problems. Contemporary analyses characterize worst-case performance by providing, under certain assumptions on an objective function, an upper bound on the number of iterations (or function or derivative evaluations) required until a pth-order stationarity condition is approximately satisfied. This arguably … Read more

    A structured quasi-Newton algorithm for optimizing with incomplete Hessian information

  • Mihai Anitescu
  • Naiyuan Chiang
  • Cosmin G. Petra
    • Categories Unconstrained Optimization Tags , , ,

    We present a structured quasi-Newton algorithm for unconstrained optimization problems that have unavailable second-order derivatives or Hessian terms. We provide a formal derivation of the well-known BFGS secant update formula that approximates only the missing Hessian terms, and we propose a line-search quasi-Newton algorithm based on a modification of Wolfe conditions that converges to first-order … Read more

    A Decision Tool based on a Multi-Objective Methodology for designing High-Pressure Thermal Treatments in Food Industry

  • Miriam R. Ferrández
  • Benjamin Ivorra
  • Pilar M. Ortigosa
  • Ángel M. Ramos
  • Juana L. Redondo
    • Categories Meta Heuristics, Optimization of Systems modeled by PDEs, Systems governed by Differential Equations Optimization Tags , , , ,

    In this work, we propose a methodology for designing High-Pressure Thermal processes for food treatment. This approach is based on a multi-objective preference-based evolutionary optimization algorithm, called WASF-GA, combined with a decision strategy which provides the food engineer with the best treatment in accordance with some quality requirements. The resulting method is compared to a … Read more

    A Shifted Primal-Dual Interior Method for Nonlinear Optimization

  • Philip E. Gill
  • Vyacheslav Kungurtsev
  • Daniel P. Robinson
    • Categories Constrained Nonlinear Optimization Tags , , , , , ,

    Interior methods provide an effective approach for the treatment of inequality constraints in nonlinearly constrained optimization. A new primal-dual interior method is proposed based on minimizing a sequence of shifted primal-dual penalty-barrier functions. Certain global convergence properties are established. In particular, it is shown that every limit point is either an infeasible stationary point, or … Read more

    An Alternating Minimization Method for Matrix Completion Problem

  • Xin Liu
  • Yuan Shen
    • Categories Convex Optimization, Unconstrained Optimization Tags , , , ,

    In this paper, we focus on solving matrix completion problem arising from applications in the fields of information theory, statistics, engineering, etc. However, the matrix completion problem involves nonconvex rank constraints which make this type of problem difficult to handle. Traditional approaches use a nuclear norm surrogate to replace the rank constraints. The relaxed model … Read more