An LMI description for the cone of Lorentz-positive maps

Let $L_n$ be the $n$-dimensional second order cone. A linear map from $\mathbb R^m$ to $\mathbb R^n$ is called positive if the image of $L_m$ under this map is contained in $L_n$. For any pair $(n,m)$ of dimensions, the set of positive maps forms a convex cone. We construct a linear matrix inequality (LMI) that … Read more

A conic interior point decomposition approach for large scale semidefinite programming

We describe a conic interior point decomposition approach for solving a large scale semidefinite programs (SDP) whose primal feasible set is bounded. The idea is to solve such an SDP using existing primal-dual interior point methods, in an iterative fashion between a {\em master problem} and a {\em subproblem}. In our case, the master problem … Read more

On the Implementation of Interior Point Decomposition Algorithms for Two-Stage Stochastic Conic

In this paper we develop a practical primal interior decomposition algorithm for two-stage stochastic programming problems. The framework of this algorithm is similar to the framework in Mehrotra and \”{Ozevin} \cite{MO04a,MO04b} and Zhao \cite{GZ01}, however their algorithm is altered in a simple yet fundamental way to achieve practical performance. In particular, this new algorithm weighs … Read more

Further Development of Multiple Centrality Correctors for Interior Point Methods

This paper addresses the role of centrality in the implementation of interior point methods. Theoretical arguments are provided to justify the use of a symmetric neighbourhood. These are translated into computational practice leading to a new insight into the role of re-centering in the implementation of interior point methods. Arguments are provided to show that … Read more

On Time-Invariant Purified-Output-Based Discrete Time Control

In http://www.optimizationonline.org/DB_HTML/2005/05/1136.html 05/25/05, we have demonstrated that the family of all affine non-anticipative output-based control laws in a discrete time linear dynamical system affected by uncertain disturbances is equivalent, as far as state-control trajectories are concerned, to the family of all affine non-anticipative “purified-output-based” control laws. The advantage of the latter representation of affine controls … Read more

A strong bound on the integral of the central path curvature and its relationship with the iteration complexity of primal-dual path-following LP algorithms

The main goals of this paper are to: i) relate two iteration-complexity bounds associated with the Mizuno-Todd-Ye predictor-corrector algorithm for linear programming (LP), and; ii) study the geometrical structure of the central path in the context of LP. The first forementioned iteration-complexity bound is expressed in terms of an integral introduced by Sonnevend, Stoer and … Read more

A Homogeneous Model for Mixed Complementarity Problems over Symmetric Cones

In this paper, we propose a homogeneous model for solving monotone mixed complementarity problems over symmetric cones, by extending the results in \cite{YOSHISE04} for standard form of the problems. We show that the extended model inherits the following desirable features: (a) A path exists, is bounded and has a trivial starting point without any regularity … Read more

Variational Two-electron Reduced Density Matrix Theory for Many-electron Atoms and Molecules: Implementation of the Spin- and Symmetry-adapted T2 Condition through First-order Semidefinite Programming

The energy and properties of a many-electron atom or molecule may be directly computed from a variational optimization of a two-electron reduced density matrix (2-RDM) that is constrained to represent many-electron quantum systems. In this paper we implement a variational 2-RDM method with a representability constraint, known as the $T_2$ condition. The optimization of the … Read more

Computational NETLIB experience with a dense projected gradient sagitta method

Computational results obtained when solving a subset of NETLIB problems by using a dense projected gradient implementation of the non-simplex active-set sagitta method presented in [12] are summarized. Two different addition rules for its initial phase are considered and, for each problem solved, two corresponding graphs are reported to illustrate the variations of the objective … Read more

Semidefinite Optimization Approaches for Satisfiability and Maximum-Satisfiability Problems

Semidefinite optimization, commonly referred to as semidefinite programming, has been a remarkably active area of research in optimization during the last decade. For combinatorial problems in particular, semidefinite programming has had a truly significant impact. This paper surveys some of the results obtained in the application of semidefinite programming to satisfiability and maximum-satisfiability problems. The … Read more