Nonlinear Optimization

Generating Cutting Inequalities Successively for Quadratic Optimization Problems in Binary Variables

  • Sunyoung Kim
  • Masakazu Kojima
    • Categories 0-1 Programming, Linear, Cone and Semidefinite Programming, Quadratic Programming Tags , , , , , , ,

    We propose a successive generation of cutting inequalities for binary quadratic optimization problems. Multiple cutting inequalities are successively generated for the convex hull of the set of the optimal solutions $\subset \{0, 1\}^n$, while the standard cutting inequalities are used for the convex hull of the feasible region. An arbitrary linear inequality with integer coefficients … Read more

    Derivative-free separable quadratic modeling and cubic regularization for unconstrained optimization

  • Ana Luisa Custódio
  • R. Garmanjani
  • Marcos Raydan
    • Categories Unconstrained Optimization Tags , , , ,

    We present a derivative-free separable quadratic modeling and cubic regularization technique for solving smooth unconstrained minimization problems. The derivative-free approach is mainly concerned with building a quadratic model that could be generated by numerical interpolation or using a minimum Frobenious norm approach, when the number of points available does not allow to build a complete … Read more

    Time-Domain Decomposition for Optimal Control Problems Governed by Semilinear Hyperbolic Systems with Mixed Two-Point Boundary Conditions

  • Richard Krug
  • Günter Leugering
  • Martin Schmidt
  • Dieter Weninger
  • Alexander Martin
    • Categories Systems governed by Differential Equations Optimization Tags , , , ,

    In this article, we continue our work (Krug et al., 2021) on time-domain decomposition of optimal control problems for systems of semilinear hyperbolic equations in that we now consider mixed two-point boundary value problems and provide an in-depth well-posedness analysis. The more general boundary conditions significantly enlarge the scope of applications, e.g., to hyperbolic problems … Read more

    An optimization problem for dynamic OD trip matrix estimation on transit networks with different types of data collection units

  • Esteve Codina
  • Lídia Montero
    • Categories Convex Optimization, Nonlinear Optimization, Transportation Tags , ,

    Dynamic O-D trip matrices for public transportation systems provide a valuable source of information of the usage of public transportation system that may be used either by planners for a better design of the transportation facilities or by the administrations in order to characterize the efficiency of the transport system both in peak hours and … Read more

    First- and second-order optimality conditions for second-order cone and semidefinite programming under a constant rank condition

  • Roberto Andreani
  • Gabriel Haeser
  • Héctor Ramírez
  • Leonardo M. Mito
  • Thiago P. Siqueira
    • Categories Constrained Nonlinear Optimization, Second-Order Cone Programming, Semi-definite Programming

    The well known constant rank constraint qualification [Math. Program. Study 21:110–126, 1984] introduced by Janin for nonlinear programming has been recently extended to a conic context by exploiting the eigenvector structure of the problem. In this paper we propose a more general and geometric approach for defining a new extension of this condition to the … Read more

    An extension of the Reformulation-Linearization Technique to nonlinear optimization

  • Danique de Moor
  • Dick den Hertog
  • Jianzhe Zhen
    • Categories Constrained Nonlinear Optimization, Global Optimization Tags , , ,

    We introduce a novel Reformulation-Perspectification Technique (RPT) to obtain convex approximations of nonconvex continuous optimization problems. RPT consists of two steps, those are, a reformulation step and a perspectification step. The reformulation step generates redundant nonconvex constraints from pairwise multiplication of the existing constraints. The perspectification step then convexifies the nonconvex components by using perspective … Read more

    Quantifying uncertainty with ensembles of surrogates for blackbox optimization

  • Charles Audet
  • Sébastien Le Digabel
  • Renaud Saltet
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization Tags , , , ,

    This work is in the context of blackbox optimization where the functions defining the problem are expensive to evaluate and where no derivatives are available. A tried and tested technique is to build surrogates of the objective and the constraints in order to conduct the optimization at a cheaper computational cost. This work proposes different … Read more

    Inexact Sequential Quadratic Optimization for Minimizing a Stochastic Objective Function Subject to Deterministic Nonlinear Equality Constraints

  • Frank E. Curtis
  • Daniel P. Robinson
  • Baoyu Zhou
    • Categories Constrained Nonlinear Optimization, Stochastic Programming Tags , , , ,

    An algorithm is proposed, analyzed, and tested experimentally for solving stochastic optimization problems in which the decision variables are constrained to satisfy equations defined by deterministic, smooth, and nonlinear functions. It is assumed that constraint function and derivative values can be computed, but that only stochastic approximations are available for the objective function and its … Read more

    A study of Liu-Storey conjugate gradient methods for vector optimization

  • Max L. N. Gonçalves
  • Leandro Fonseca Prudente
  • F. S. Lima
    • Categories Multi-Criteria Optimization, Unconstrained Optimization Tags , , ,

    This work presents a study of Liu-Storey (LS) nonlinear conjugate gradient (CG) methods to solve vector optimization problems. Three variants of the LS-CG method originally designed to solve single-objective problems are extended to the vector setting. The first algorithm restricts the LS conjugate parameter to be nonnegative and use a sufficiently accurate line search satisfying … Read more

    A framework for convex-constrained monotone nonlinear equations and its special cases

  • Max L. N. Gonçalves
  • Tiago Menezes
    • Categories Nonlinear Systems and Least-Squares

    This work refers to methods for solving convex-constrained monotone nonlinear equations. We first propose a framework, which is obtained by combining a safeguard strategy on the search directions with a notion of approximate projections. The global convergence of the framework is established under appropriate assumptions and some examples of methods which fall into this framework … Read more