Xinxin Li

A Semismooth Newton-Type Method for the Nearest Doubly Stochastic Matrix Problem

  • Hao Hu
  • Xinxin Li
  • Henry Wolkowicz
  • Haesol Im
    • Categories Convex and Nonsmooth Optimization, Nonsmooth Optimization Tags , , , ,

    We study a semismooth Newton-type method for the nearest doubly stochastic matrix problem where both differentiability and nonsingularity of the Jacobian can fail. The optimality conditions for this problem are formulated as a system of strongly semismooth functions. We show that the so-called local error bound condition does not hold for this system. Thus the … Read more

    A Restricted Dual Peaceman-Rachford Splitting Method for QAP

  • Naomi Graham
  • Hao Hu
  • Xinxin Li
  • Henry Wolkowicz
  • Haesol Im
    • Categories (Mixed) Integer Nonlinear Programming, Linear, Cone and Semidefinite Programming, Optimization Software Benchmark Tags , , , ,

    We revisit and strengthen splitting methods for solving doubly nonnegative, DNN, relaxations of the quadratic assignment problem, QAP. We use a modified restricted contractive splitting method, rPRSM, approach. Our strengthened bounds and new dual multiplier estimates improve on the bounds and convergence results in the literature. CitationDepartment of Combinatorics & Optimization, University of Waterloo, Canada,06/2019ArticleDownload … Read more

    A Strictly Contractive Peaceman-Rachford Splitting Method for the Doubly Nonnegative Relaxation of the Minimum Cut Problem

  • Xinxin Li
  • Ting Kei Pong
  • Hao Sun
  • Henry Wolkowicz
    • Categories (Mixed) Integer Nonlinear Programming, Linear, Cone and Semidefinite Programming, Optimization Software Benchmark Tags , , , , , ,

    The minimum cut problem, MC, and the special case of the vertex separator problem, consists in partitioning the set of nodes of a graph G into k subsets of given sizes in order to minimize the number of edges cut after removing the k-th set. Previous work on this topic uses eigenvalue, semidefinite programming, SDP, … Read more