A fix-and-relax heuristic for controlled tabular adjustment

Controlled tabular adjustment (CTA) is an emerging protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is tough for tables of moderate size. Finding a feasible initial solution may even be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give … Read more

A direct splitting method for nonsmooth variational inequalities

We propose a direct splitting method for solving nonsmooth variational inequality problems in Hilbert spaces. The weak convergence is established, when the operator is the sum of two point-to-set and monotone operators. The proposed method is a natural extension of the incremental subgradient method for nondifferentiable optimization, which explores strongly the structure of the operator … Read more

Temporal vs. Stochastic Granularity in Thermal Generation Capacity Planning with Wind Power

We propose a stochastic generation expansion model, where we represent the long-term uncertainty in the availability and variability in the weekly wind pattern with multiple scenarios. Scenario reduction is conducted to select a representative set of scenarios for the long-term wind power uncertainty. We assume that the short-term wind forecast error induces an additional amount … Read more

Analysis of Copositive Optimization Based Linear Programming Bounds on Standard Quadratic Optimization

The problem of minimizing a quadratic form over the unit simplex, referred to as a standard quadratic optimization problem, admits an exact reformulation as a linear optimization problem over the convex cone of completely positive matrices. This computationally intractable cone can be approximated from the inside and from the outside by two sequences of nested … Read more

A comparison of routing sets for robust network design

Designing a network able to route a set of non-simultaneous demand vectors is an important problem arising in telecommunications. In this paper, we compare the optimal capacity allocation costs for six routing sets: affine routing, volume routing and its two simplifications, the routing based on an unrestricted 2-cover of the uncertainty set, and the routing … Read more

Stochastic linear programming games with concave preferences

We study stochastic linear programming games: a class of stochastic cooperative games whose payoffs under any realization of uncertainty are determined by a specially structured linear program. These games can model a variety of settings, including inventory centralization and cooperative network fortification. We focus on the core of these games under an allocation scheme that … Read more

Nonsmooth Algorithms and Nesterov’s Smoothing Techniques for Generalized Fermat-Torricelli Problems

In this paper we present some algorithms for solving a number of new models of facility location involving sets which generalize the classical Fermat-Torricelli problem. Our approach uses subgradient-type algorithms to cope with nondi erentiabilty of the distance functions therein. Another approach involves approximating nonsmooth optimization problems by smooth optimizations problems using Nesterov’s smoothing techniques. Convergence … Read more

Fabrication-Adaptive Optimization, with an Application to Photonic Crystal Design

It is often the case that the computed optimal solution of an optimization problem cannot be implemented directly, irrespective of data accuracy, due to either (i) technological limitations (such as physical tolerances of machines or processes), (ii) the deliberate simplification of a model to keep it tractable (by ignoring certain types of constraints that pose … Read more

The Freight Train Routing Problem

We consider the following freight train routing problem (FTRP). Given is a transportation network with fixed routes for passenger trains and a set of freight trains (requests), each defined by an origin and destination station pair. The objective is to calculate a feasible route for each freight train such that a sum of all expected … Read more

Exploiting total unimodularity for classes of random network problems

Network analysis is of great interest for the study of social, biological and technological networks, with applications, among others, in business, marketing, epidemiology and telecommunications. Researchers are often interested in assessing whether an observed feature in some particular network is expected to be found within families of networks under some hypothesis (named conditional random networks, … Read more