A binary LP model to the facility layout problem

In facility layout problems, a major concern is the optimal design or remodeling of the facilities of an organization. The decision-maker’s objective is to arrange the facility in an optimal way, so that the interaction among functions (i.e. machines, inventories, persons) and places (i.e. offices, work locations, depots) is efficient. A simple pure-binary LP model … Read more

The least-intensity feasible solution for aperture-based inverse planning in radiation therapy.

Aperture-based inverse planning (ABIP) for intensity modulated radiation therapy (IMRT) treatment planning starts with external radiation fields (beams) that fully conform to the target(s) and then superimposes sub-fields called segments to achieve complex shaping of 3D dose distributions. The segments’ intensities are determined by solving a feasibility problem. The least-intensity feasible (LIF) solution, proposed and … Read more

A New Mathematical-Programming Framework for Facility-Layout Design

We present a new framework for efficiently finding competitive solutions for the facility-layout problem. This framework is based on the combination of two new mathematical-programming models. The first model is a relaxation of the layout problem and is intended to find good starting points for the iterative algorithm used to solve the second model. The … Read more

Large-Scale Linear Programming Techniques for the Design of Protein Folding Potentials

We present large-scale optimization techniques to model the energy function that underlies the folding process of proteins. Linear Programming is used to identify parameters in the energy function model, the objective being that the model predict the structure of known proteins correctly. Such trained functions can then be used either for {\em ab-initio} prediction or … Read more

Space mapping: Models, sensitivities, and trust-regions methods

The goal of this paper is to organize some of the mathematical and algorithmic aspects of the recently proposed space-mapping technique for continuous optimization with expensive function evaluations. First, we consider the mapping from the fine space to the coarse space when the models are vector-valued functions and when the space-mapping (nonlinear) least-squares residual is … Read more

Bounds on measures satisfying moment conditions

Given a semi algebraic set S of R^n we provide a numerical approximation procedure that yields upper and lower bounds on mu(S), for measures mu that satisfy some given moment conditions. The bounds are obtained as solutions of positive semidefinite programs that can be solved via standard software packages like the LMI MATLAB toolbox. Citation … Read more

The Maximum Box Problem and its Application to Data Analysis

Given two finite sets of points $X^+$ and $X^-$ in $\R^n$, the maximum box problem consists in finding an interval (“box”) $B=\{x : l \leq x \leq u\}$ such that $B\cap X^-=\emptyset$, and the cardinality of $B\cap X^+$ is maximized. A simple generalization can be obtained by instead maximizing a weighted sum of the elements … Read more

[PENNON – A Generalized Augmented Lagrangian Methodfor Semidefinite Programming

This article describes a generalization of the PBM method by Ben-Tal and Zibulevsky to convex semidefinite programming problems. The algorithm used is a generalized version of the Augmented Lagrangian method. We present details of this algorithm as implemented in a new code PENNON. The code can also solve second-order conic programming (SOCP) problems, as well … Read more

Power transmission network design by a greedy randomized adaptive path relinking approach

This paper illustrates results obtained by a new metaheuristic approach, Greedy Randomized Adaptive Path Relinking, applied to solve static power transmission network design problems. This new approach consists of a generalization of GRASP concepts to explore different trajectories between two Citation AT&T Labs Research Report, December 2001 Submitted to PSCC’02. Article Download View Power transmission … Read more

New Versions of Interior Point Methods Applied to the Optimal Power Flow Problem

Interior Point methods for Nonlinear Programming have been extensively used to solve the Optimal Power Flow problem. These optimization algorithms require the solution of a set of nonlinear equations to obtain the optimal solution of the power network equations. During the iterative process to solve these equations, the search for the optimum is based on … Read more