Jong-Shi Pang

A Study of the Difference-of-Convex Approach for Solving Linear Programs with Complementarity Constraints

  • Francisco Jara-Moroni
  • Jong-Shi Pang
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization Tags , , ,

    This paper studies the difference-of-convex (DC) penalty formulations and the associated difference-of-convex algorithm (DCA) for computing stationary solutions of linear programs with complementarity constraints (LPCCs). We focus on three such formulations and establish connections between their stationary solutions and those of the LPCC. Improvements of the DCA are proposed to remedy some drawbacks in a … Read more

    On QPCCs, QCQPs and Completely Positive Programs

  • Lijie Bai
  • John E. Mitchell
  • Jong-Shi Pang
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization, Linear, Cone and Semidefinite Programming

    This paper studies several classes of nonconvex optimization problems defined over convex cones, establishing connections between them and demonstrating that they can be equivalently formulated as convex completely positive programs. The problems being studied include: a quadratically constrained quadratic program (QCQP), a quadratic program with complementarity constraints (QPCC), and rank constrained semidefinite programs. Our results … Read more

    Complementarity Formulations of l0-norm Optimization Problems

  • Mingbin Feng
  • John E. Mitchell
  • Jong-Shi Pang
  • Xin Shen
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization Tags , ,

    In a number of application areas, it is desirable to obtain sparse solutions. Minimizing the number of nonzeroes of the solution (its l0-norm) is a difficult nonconvex optimization problem, and is often approximated by the convex problem of minimizing the l1-norm. In contrast, we consider exact formulations as mathematical programs with complementarity constraints and their … Read more

    Subspace accelerated matrix splitting algorithms for bound-constrained quadratic programming and linear complementarity problems

  • Liming Feng
  • Jorge Nocedal
  • Daniel P. Robinson
  • Jong-Shi Pang
    • Categories Bound-constrained Optimization, Finance and Economics Tags , , , , , , ,

    This paper studies the solution of two problems—bound-constrained quadratic programs and linear complementarity problems—by two-phase methods that consist of an active set prediction phase and a subspace phase. The algorithms enjoy favorable convergence properties under weaker assumptions than those assumed for other methods in the literature. The active set prediction phase employs matrix splitting iterations … Read more

    An LPCC Approach to Nonconvex Quadratic Programs

  • Jing Hu
  • John E. Mitchell
  • Jong-Shi Pang
    • Categories Complementarity and Variational Inequalities, Quadratic Programming Tags , , ,

    Filling a gap in nonconvex quadratic programming, this paper shows that the global resolution of a feasible quadratic program (QP), which is not known a priori to be bounded or unbounded below, can be accomplished in finite time by solving a linear program with linear complementarity constraints, i.e., an LPCC. Alternatively, this task can be … Read more

    On the Global Solution of Linear Programs with Linear Complementarity Constraints

  • Kristin P. Bennett
  • Jing Hu
  • John E. Mitchell
  • Gautam Kunapuli
  • Jong-Shi Pang
    • Categories Complementarity and Variational Inequalities

    This paper presents a parameter-free integer-programming based algorithm for the global resolution of a linear program with linear complementarity constraints (LPEC). The cornerstone of the algorithm is a minimax integer program formulation that characterizes and provides certificates for the three outcomes—infeasibility, unboundedness, or solvability—of an LPEC. An extreme point/ray generation scheme in the spirit of … Read more

    On the Global Minimization of the Value-at-Risk

  • Sven Leyffer
  • Jong-Shi Pang
    • Categories Complementarity and Variational Inequalities, Global Optimization, Nonlinear Optimization

    In this paper, we consider the nonconvex minimization problem of the value-at-risk (VaR) that arises from financial risk analysis. By considering this problem as a special linear program with linear complementarity constraints (a bilevel linear program to be more precise), we develop upper and lower bounds for the minimum VaR and show how the combined … Read more