A priori bounds on the condition numbers in interior-point methods

Interior-point methods are known to be sensitive to ill-conditioning and to scaling of the data. This paper presents new asymptotically sharp bounds on the condition numbers of the linear systems at each iteration of an interior-point method for solving linear or semidefinite programs and discusses a stopping test which leads to a problem-independent “a priori” … Read more

Thermal Optimization of the Continuous Casting Process using Distributed Parameter Identification Approach — Controlling the Curvature of Solid-Liquid Interface

Thermal optimization of vertical continuous casting process is considered in the present study. The goal is to find the optimal distribution of temperature and interfacial heat transfer coefficients corresponding to the primary and secondary cooling systems, in addition to the pulling speed, such that the solidification along the main axis of strand approaches to the … Read more

Low-rank spectral optimization

Various applications in signal processing and machine learning give rise to highly structured spectral optimization problems characterized by low-rank solutions. Two important examples that motivate this work are optimization problems from phase retrieval and from blind deconvolution, which are designed to yield rank-1 solutions. An algorithm is described based solving a certain constrained eigenvalue optimization … Read more

Semi-Online Scheduling on Two Uniform Machines with Known Optimum, Part II: Tight Upper Bounds

We consider a semi-online version of the problem of scheduling a sequence of jobs of different lengths on two uniform machines with given speeds $1$ and $s$. Jobs are revealed one by one (the assignment of a job has to be done before the next job is revealed), and the objective is to minimize the … Read more

Semi-Online Scheduling on Two Uniform Machines with Known Optimum, Part I: Tight Lower Bounds

This problem is about to schedule a number of jobs of different lengths on two uniform machines with given speeds $1$ and $s \geq 1$, so that the overall completion time, i.e., the makespan, is earliest possible. We consider a semi-online variant (introduced for equal speeds) by Azar and Regev, where the jobs arrive one … Read more

New Valid Inequalities and Facets for the Simple Plant Location Problem

The Simple Plant Location Problem is a well-known (and NP-hard) combinatorial optimisation problem, with applications in logistics. We present a new family of valid inequalities for the associated family of polyhedra, and show that it contains an exponentially large number of new facet-defining members. We also present a new procedure, called facility augmentation, which enables … Read more

Mixed Integer Second-Order Cone Programming for the Horizontal and Vertical Free-flight Planning Problem

In the past, travel routes for civil passenger and cargo air traffic were aligned to the air traffic network (ATN). To resolve the network congestion problem, the free-flight system has recently been introduced in more and more regions around the globe, allowing flight operations to make full use of the four space-and-time dimensions. For the … Read more

Dominance in Pricing Problems with Stochasticity

Sequencing activities over time is a fundamental optimization problem. The problem can be modeled using a directed network in which activities are represented by nodes and pairs of activities that can be performed consecutively are represented by arcs. A sequence of activities then corresponds to a path in the directed network, and an optimal sequence … Read more

On the Convergence of Multi-Block Alternating Direction Method of Multipliers and Block Coordinate Descent Method

The paper answers several open questions of the alternating direction method of multipliers (ADMM) and the block coordinate descent (BCD) method that are now wildly used to solve large scale convex optimization problems in many fields. For ADMM, it is still lack of theoretical understanding of the algorithm when the objective function is not separable … Read more

Diffusion Methods for Classification with Pairwise Relationships

We define two algorithms for propagating information in classification problems with pairwise relationships. The algorithms involve contraction maps and are related to non-linear diffusion and random walks on graphs. The approach is also related to message passing and mean field methods. The algorithms we describe are guaranteed to converge on graphs with arbitrary topology. Moreover … Read more