On the optimal order of worst case complexity of direct search

The worst case complexity of direct-search methods has been recently analyzed when they use positive spanning sets and impose a sufficient decrease condition to accept new iterates. Assuming that the objective function is smooth, it is now known that such methods require at most O(n^2 epsilon^{-2}) function evaluations to compute a gradient of norm below … Read more

An electronic compendium of extreme functions for the Gomory–Johnson infinite group problem

In this note we announce the availability of an electronic compendium of extreme functions for Gomory–Johnson’s infinite group problem. These functions serve as the strongest cut-generating functions for integer linear optimization problems. We also close several gaps in the literature. Article Download View An electronic compendium of extreme functions for the Gomory–Johnson infinite group problem

Simplex Algorithm for Countable-state Discounted Markov Decision Processes

We consider discounted Markov Decision Processes (MDPs) with countably-infinite state spaces, finite action spaces, and unbounded rewards. Typical examples of such MDPs are inventory management and queueing control problems in which there is no specific limit on the size of inventory or queue. Existing solution methods obtain a sequence of policies that converges to optimality … Read more

The direct extension of ADMM for three-block separable convex minimization models is convergent when one function is strongly convex

The alternating direction method of multipliers (ADMM) is a benchmark for solving a two-block linearly constrained convex minimization model whose objective function is the sum of two functions without coupled variables. Meanwhile, it is known that the convergence is not guaranteed if the ADMM is directly extended to a multiple-block convex minimization model whose objective … Read more

Solution Analysis for the Pseudomonotone Second-order Cone Linear Complementarity Problem

In this paper, we study properties of the solution of the pseudomonotone second-order cone linear complementarity problems (SOCLCP). Based upon Tao’s recent work [Tao, J. Optim. Theory Appl., 159(2013), pp. 41–56] on pseudomonotone LCP on Euclidean Jordan algebras, we made two noticeable contributions on the solutions of the pseudomonotone SOCLCP: First, we introduce the concept … Read more

A Filter Active-Set Algorithm for Ball/Sphere Constrained Optimization Problem

In this paper, we propose a filter active-set algorithm for the minimization problem over a product of multiple ball/sphere constraints. By making effective use of the special structure of the ball/sphere constraints, a new limited memory BFGS (L-BFGS) scheme is presented. The new L-BFGS implementation takes advantage of the sparse structure of the Jacobian of … Read more

Convex hull of two quadratic or a conic quadratic and a quadratic inequality

In this paper we consider an aggregation technique introduced by Yildiran, 2009 to study the convex hull of regions defined by two quadratic or by a conic quadratic and a quadratic inequality. Yildiran shows how to characterize the convex hull of open sets defined by two strict quadratic inequalities using Linear Matrix Inequalities (LMI). We … Read more

On proximal subgradient splitting method for minimizing the sum of two nonsmooth convex functions

In this paper we present a variant of the proximal forward-backward splitting method for solving nonsmooth optimization problems in Hilbert spaces, when the objective function is the sum of two nondifferentiable convex functions. The proposed iteration, which will be call the Proximal Subgradient Splitting Method, extends the classical projected subgradient iteration for important classes of … Read more

A specialized branch-and-bound algorithm for the Euclidean Steiner tree problem in n-space

We present a specialized branch-and-bound (b&b) algorithm for the Euclidean Steiner tree problem (ESTP) in R^n and apply it to a convex mixed-integer nonlinear programming (MINLP) formulation of the problem, presented by Fampa and Maculan. The algorithm contains procedures to avoid difficulties observed when applying a b&b algorithm for general MINLP problems to solve the … Read more

A trust-region method for box-constrained nonlinear semidefinite programs

We propose a trust-region method for nonlinear semidefinite programs with box-constraints. The penalty barrier method can handle this problem, but the size of variable matrices available in practical time is restricted to be less than 500. We develop a trust-region method based on the approach of Coleman and Li (1996) that utilizes the distance to … Read more