Nonlinear Optimization

A Trust Region Algorithm with a Worst-Case Iteration Complexity of ${\cal O}(\epsilon^{-3/2})$ for Nonconvex Optimization

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

    We propose a trust region algorithm for solving nonconvex smooth optimization problems. For any $\bar\epsilon \in (0,\infty)$, the algorithm requires at most $\mathcal{O}(\epsilon^{-3/2})$ iterations, function evaluations, and derivative evaluations to drive the norm of the gradient of the objective function below any $\epsilon \in (0,\bar\epsilon]$. This improves upon the $\mathcal{O}(\epsilon^{-2})$ bound known to hold for … Read more

    High Detail Stationary Optimization Models for Gas Networks: Validation and Results

  • Martin Schmidt
  • Marc C. Steinbach
  • Bernhard M. Willert
    • Categories Applications - Science and Engineering, Constrained Nonlinear Optimization, Systems governed by Differential Equations Optimization Tags , , ,

    Due to strict regulatory rules in combination with complex nonlinear physics, major gas network operators in Germany and Europe face hard planning problems that call for optimization. In part 1 of this paper we have developed a suitable model hierarchy for that purpose. Here we consider the more practical aspects of modeling. We validate individual … Read more

    Iteration Bounds for Finding the $\epsilonhBcStationary Points for Structured Nonconvex Optimization

  • Bo Jiang
  • Shuzhong Zhang
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization Tags , , ,

    In this paper we study proximal conditional-gradient (CG) and proximal gradient-projection type algorithms for a block-structured constrained nonconvex optimization model, which arises naturally from tensor data analysis. First, we introduce a new notion of $\epsilon$-stationarity, which is suitable for the structured problem under consideration. %, compared with other similar solution concepts. We then propose two … Read more

    On an inexact trust-region SQP-filter method for constrained nonlinear optimization

  • Lorenz T. Biegler
  • Andrea Walther
    • Categories Constrained Nonlinear Optimization Tags , ,

    A class of trust-region algorithms is developed and analyzed for the solution of optimization problems with nonlinear equality and inequality constraints. Based on composite-step trust region methods and a filter approach, the resulting algorithm also does not require the computation of exact Jacobians; only Jacobian vector products are used along with approximate Jacobian matrices. As … Read more

    A Flexible Iterative Solver for Nonconvex, Equality-Constrained Quadratic Subproblems

  • Alp Dener
  • Jason Hicken
    • Categories Constrained Nonlinear Optimization, Multidisciplinary Design Optimization, Optimization of Systems modeled by PDEs Tags , , , , ,

    We present an iterative primal-dual solver for nonconvex equality-constrained quadratic optimization subproblems. The solver constructs the primal and dual trial steps from the subspace generated by the generalized Arnoldi procedure used in flexible GMRES (FGMRES). This permits the use of a wide range of preconditioners for the primal-dual system. In contrast with FGMRES, the proposed … Read more

    Weak and Strong Superiorization: Between Feasibility-Seeking and Minimization

  • Yair Censor
    • Categories Constrained Nonlinear Optimization, Convex Optimization

    We review the superiorization methodology, which can be thought of, in some cases, as lying between feasibility-seeking and constrained minimization. It is not quite trying to solve the full fledged constrained minimization problem; rather, the task is to find a feasible point which is superior (with respect to an objective function value) to one returned … Read more

    Majorization-minimization procedures and convergence of SQP methods for semi-algebraic and tame programs

  • Jérôme Bolte
  • Edouard Pauwels
    • Categories Applications - Science and Engineering, Nonlinear Optimization Tags , , , , , , , ,

    In view of solving nonsmooth and nonconvex problems involving complex constraints (like standard NLP problems), we study general maximization-minimization procedures produced by families of strongly convex sub-problems. Using techniques from semi-algebraic geometry and variational analysis –in particular Lojasiewicz inequality– we establish the convergence of sequences generated by this type of schemes to critical points. The … Read more

    Lower Bounds for the Quadratic Minimum Spanning Tree Problem Based on Reduced Cost Computation

  • Federico Malucelli
  • Borzou Rostami
    • Categories Combinatorial Optimization, Quadratic Programming Tags , , , , ,

    The Minimum Spanning Tree Problem (MSTP) is one of the most known combinatorial optimization problems. It concerns the determination of a minimum edge-cost subgraph spanning all the vertices of a given connected graph. The Quadratic Minimum Spanning Tree Problem (QMSTP) is a variant of the MST whose cost considers also the interaction between every pair … Read more

    An Inertia-Free Filter Line-Search Algorithm for Large-Scale Nonlinear Programming

  • Naiyuan Chiang
  • Victor M. Zavala
    • Categories Nonlinear Optimization, Optimization of Systems modeled by PDEs, Stochastic Programming Tags , , , ,

    We present a filter line-search algorithm that does not require inertia information about the linear system to ensure global convergence. The proposed approach performs curvature tests along the search step to ensure descent. This feature permits more modularity in the linear algebra, enabling the use of a wider range of iterative and decomposition strategies. We … Read more

    A collision detection approach for maximizing the material utilization

  • Volker Maag
    • Categories Constrained Nonlinear Optimization, Semi-infinite Programming Tags , , , ,

    We introduce a new method for a task of maximal material utilization, which is is to fit a flexible, scalable three-dimensional body into another aiming for maximal volume whereas position and shape may vary. The difficulty arises from the containment constraint which is not easy to handle numerically. We use a collision detection method to … Read more