interior point methods

Nonlinear Derivative-free Constrained Optimization with a Mixed Penalty-Logarithmic Barrier Approach and Direct Search

  • Andrea Brilli
  • Ana Luisa Custódio
  • Giampaolo Liuzzi
  • Everton Silva
    • Categories Constrained Nonlinear Optimization Tags , , ,

    In this work, we propose the joint use of a mixed penalty-logarithmic barrier approach and generating set search, for addressing nonlinearly constrained derivative-free optimization problems. A merit function is considered, wherein the set of inequality constraints is divided into two groups: one treated with a logarithmic barrier approach, and another, along with the equality constraints, … Read more

    A hybrid branch-and-bound and interior-point algorithm for stochastic mixed-integer nonlinear second-order cone programming

  • Baha Alzalg
    • Categories (Mixed) Integer Nonlinear Programming, Cutting Plane Approaches, Second-Order Cone Programming Tags , , , ,

    One of the chief attractions of stochastic mixed-integer second-order cone programming is its diverse applications, especially in engineering (Alzalg and Alioui, {\em IEEE Access}, 10:3522-3547, 2022). The linear and nonlinear versions of this class of optimization problems are still unsolved yet. In this paper, we develop a hybrid optimization algorithm coupling branch-and-bound and primal-dual interior-point … Read more

    Riemannian Interior Point Methods for Constrained Optimization on Manifolds

  • Zhijian Lai
  • Akiko Yoshise
    • Categories Linear, Cone and Semidefinite Programming, Nonlinear Optimization Tags , , , , ,

    We extend the classical primal-dual interior point method from the Euclidean setting to the Riemannian one. Our method, named the Riemannian interior point method (RIPM), is for solving Riemannian  constrained optimization problems. We establish its local superlinear and quadratic convergence  under the standard assumptions. Moreover, we show its global convergence when it is combined with … Read more

    A semidefinite programming approach for the projection onto the cone of negative semidefinite symmetric tensors with applications to solid mechanics

  • Cristina Padovani
  • Margherita Porcelli
    • Categories Civil and Environmental Engineering, Linear, Cone and Semidefinite Programming Tags , , ,

    We propose an algorithm for computing the projection of a symmetric second-order tensor onto the cone of negative semidefinite symmetric tensors with respect to the inner product defined by an assigned positive definite symmetric fourth-order tensor C. The projection problem is written as a semidefinite programming problem and an algorithm based on a primal-dual path-following … Read more

    A barrier Lagrangian dual method for multi-stage stochastic convex semidefinite optimization

  • Baha Alzalg
  • Asma Gafour
    • Categories Nonlinear Optimization, Semi-definite Programming, Stochastic Programming Tags , , , ,

    In this paper, we present a polynomial-time barrier algorithm for solving multi-stage stochastic convex semidefinite optimization based on the Lagrangian dual method which relaxes the nonanticipativity constraints. We show that the barrier Lagrangian dual functions for our setting form self-concordant families with respect to barrier parameters. We also use the barrier function method to improve … Read more

    On solving large-scale multistage stochastic problems with a new specialized interior-point approach

  • Jordi Castro
  • Laureano F. Escudero
  • Juan F. Monge
    • Categories Linear, Cone and Semidefinite Programming, Stochastic Programming Tags , , , , ,

    A novel approach based on a specialized interior-point method (IPM) is presented for solving large-scale stochastic multistage continuous optimization problems, which represent the uncertainty in strategic multistage and operational two-stage scenario trees, the latter being rooted at the strategic nodes. This new solution approach considers a split-variable formulation of the strategic and operational structures, for … 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

    Algebraic-based primal interior-point algorithms for stochastic infinity norm optimization

  • Baha Alzalg
  • Karima Tamsaouete
    • Categories Linear, Cone and Semidefinite Programming, Nonlinear Optimization, Stochastic Programming Tags , , , ,

    We study the two-stage stochastic infinity norm optimization problem with recourse. First, we study and analyze the algebraic structure of the infinity norm cone, and use its algebra to compute the derivatives of the barrier recourse functions. Then, we show that the barrier recourse functions and the composite barrier functions for this optimization problem are … Read more

    An Improved Penalty Algorithm using Model Order Reduction for MIPDECO problems with partial observations

  • Dominik Garmatter
  • Margherita Porcelli
  • Francesco Rinaldi
  • Martin Stoll
    • Categories (Mixed) Integer Nonlinear Programming, Optimization of Systems modeled by PDEs Tags , , , ,

    This work addresses optimal control problems governed by a linear time-dependent partial differential equation (PDE) as well as integer constraints on the control. Moreover, partial observations are assumed in the objective function. The resulting problem poses several numerical challenges due to the mixture of combinatorial aspects, induced by integer variables, and large scale linear algebra … Read more

    A new stopping criterion for Krylov solvers applied in Interior Point Methods

  • Jacek Gondzio
  • Filippo Zanetti
    • Categories Convex Optimization Tags , , , ,

    A surprising result is presented in this paper with possible far reaching consequences for any optimization technique which relies on Krylov subspace methods employed to solve the underlying linear equation systems. In this paper the advantages of the new technique are illustrated in the context of Interior Point Methods (IPMs). When an iterative method is … Read more