Superlinear convergence of an infeasible interior point algorithm on the homogeneous feasibility model of a semi-definite program

In the literature, superlinear convergence of implementable polynomial-time interior point algorithms to solve semi-definite programs (SDPs) can only be shown by (i) assuming that the given SDP is nondegenerate and modifying these algorithms, or (ii) considering special classes of SDPs, such as the class of linear semi-definite feasibility problems, when a suitable initial iterate is … Read more

Solution to a Monotone Inclusion Problem using the Relaxed Peaceman-Rachford Splitting Method: Convergence and its Rates

We consider the convergence behavior using the relaxed Peaceman-Rachford splitting method to solve the monotone inclusion problem $0 \in (A + B)(u)$, where $A, B: \Re^n \rightrightarrows \Re^n$ are maximal $\beta$-strongly monotone operators, $n \geq 1$ and $\beta > 0$. Under a technical assumption, convergence of iterates using the method on the problem is proved … Read more

A FISTA-type first order algorithm on composite optimization problems that is adaptable to the convex situation

In this note, we propose a FISTA-type first order algorithm, VAR-FISTA, to solve a composite optimization problem. A distinctive feature of VAR-FISTA is its ability to exploit the convexity of the function in the problem, resulting in an improved iteration complexity when the function is convex compared to when it is nonconvex. The iteration complexity … Read more

A FISTA-type accelerated gradient algorithm for solving smooth nonconvex composite optimization problems

In this paper, we describe and establish iteration-complexity of two accelerated composite gradient (ACG) variants to solve a smooth nonconvex composite optimization problem whose objective function is the sum of a nonconvex differentiable function f with a Lipschitz continuous gradient and a simple nonsmooth closed convex function h. When f is convex, the first ACG … Read more

Interior Point Method on Semi-definite Linear Complementarity Problems using the Nesterov-Todd (NT) Search Direction: Polynomial Complexity and Local Convergence

We consider in this paper an infeasible predictor-corrector primal-dual path following interior point algorithm using the Nesterov-Todd (NT) search direction to solve semi-definite linear complementarity problems. Global convergence and polynomial iteration complexity of the algorithm are established. Two sufficient conditions are also given for superlinear convergence of iterates generated by the algorithm. Preliminary numerical results … Read more

Policies for Inventory Models with Product Returns Forecast from Past Demands and Past Sales

Finite horizon periodic review backlog models are considered in this paper for an inventory system that remanufactures two types of cores: buyback cores and normal cores. Returns of used products as buyback cores are modelled to depend on past demands and past sales. We obtain an optimal inventory policy for the model in which returns … Read more

Complexity of the relaxed Peaceman-Rachford splitting method for the sum of two maximal strongly monotone operators

This paper considers the relaxed Peaceman-Rachford (PR) splitting method for fi nding an approximate solution of a monotone inclusion whose underlying operator consists of the sum of two maximal strongly monotone operators. Using general results obtained in the setting of a non-Euclidean hybrid proximal extragradient framework, convergence of the iterates, as well as pointwise and ergodic … Read more

Infinite horizon optimal policy for an inventory system with two types of products sharing common hardware platforms

We consider a periodic review inventory system and present its optimal policy in the infinite horizon setting. The optimal inventory policy that maximizes the infinite horizon expected discount profit for the model is analytically obtained by relating to the finite horizon setting using results from variational analysis. Results are provided that elucidate the operations of … Read more

On Finding a Generalized Lowest Rank Solution to a Linear Semi-definite Feasibility Problem

In this note, we generalize the affine rank minimization problem and the vector cardinality minimization problem and show that the resulting generalized problem can be solved by solving a sequence of continuous concave minimization problems. In the case of the vector cardinality minimization problem, we show that it can be solved by solving the continuous … Read more

A Note on Superlinear Convergence of a Primal-dual Interior Point Method for Nonlinear Semi-definite Programming

We replace one of the assumptions (nondegeneracy assumption) in [9] to show that the main results in [9] still hold. We also provide a simple example to show that the new assumption is satisfied, while the original assumption is not satisfied, with other assumptions being satisfied. This example shows that the new assumption does not … Read more