Lifting Inequalities: A framework for generating strong cuts in nonlinear programs

In this paper, we propose lifting techniques for generating strong cuts for nonlinear programs that are globally-valid. The theory is geometric and provides intuition into lifting-based cut generation procedures. As a special case, we find short proofs of earlier results on lifting techniques for mixed-integer programs. Using convex extensions, we obtain conditions that allow sequence-independent … Read more

Generating All Efficient Extreme Points in Multiple Objective Linear Programming Problem and Its Application

In this paper, simple linear programming procedure is proposed for generating all efficient extreme points and all efficient extreme rays of a multiple objective linear programming problem (V P). As an application we solve the linear multiplicative programming associated with the problem (VP). CitationsubmittedArticleDownload View PDF

Another Face of DIRECT

It is shown that, contrary to a claim of [D. E. Finkel, and C. T. Kelley, Additive scaling and the DIRECT algorithm, J. Glob. Optim. 36 (2006) 597-608], it is possible to divide the smallest hypercube which contains the low function value by considering hyperrectangles whose points are located on the diagonal of the center … Read more

Iterative Minimization Schemes for Solving the Single Source Localization Problem

We consider the problem of locating a single radiating source from several noisy measurements using a maximum likelihood (ML) criteria. The resulting optimization problem is nonconvex and nonsmooth and thus finding its global solution is in principal a hard task. Exploiting the special structure of the objective function, we introduce and analyze two iterative schemes … Read more

Outcome-Space Outer Approximation Algorithm for Linear Multiplicative Programming

This paper presents an outcome-space outer approximation algorithm for globally solving the linear multiplicative programming problem. We prove that the proposed algorithm is finite. To illustrate the new algorithm, we apply it to solve some sample problems. Citation10, Hanoi University of Technology, 07/2007ArticleDownload View PDF

Stopping Rules for Box-Constrained Stochastic Global Optimization

We present three new stopping rules for Multistart based methods. The first uses a device that enables the determination of the coverage of the bounded search domain. The second is based on the comparison of asymptotic expectation values of observable quantities to the actually measured ones. The third offers a probabilistic estimate for the number … Read more

Comments on “Dual Methods for Nonconvex Spectrum Optimization of Multicarrier Systems”

Yu and Liu’s strong duality theorem under the time-sharing property requires the Slater condition to hold for the considered general nonconvex problem, what is satisfied for the specific application. We further extend the scope of the theorem under Ky Fan convexity which is slightly weaker than Yu&Lui’s time-sharing property. ArticleDownload View PDF

Optimization for Simulation: LAD Accelerator

The goal of this paper is to address the problem of evaluating the performance of a system running under unknown values for its stochastic parameters. A new approach called LAD for Simulation, based on simulation and classification software, is presented. It uses a number of simulations with very few replications and records the mean value … Read more

Max-min separability: incremental approach and application to supervised data classification

A new algorithm for the computation of a piecewise linear function separating two finite point sets in $n$-dimensional space is developed and the algorithm is applied to solve supervised data classification problems. The algorithm computes hyperplanes incrementally and it finds as many hyperplanes as necessary to separate two sets with respect to some tolerance. An … Read more