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Nonconvex Optimization and Its Applications
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Derivative-free optimization: a review of algorithms and comparison of software implementations
TL;DR: It is found that the ability of all these solvers to obtain good solutions diminishes with increasing problem size, and TomLAB/MULTIMIN, TOMLAB/GLCCLUSTER, MCS and TOMLab/LGO are better, on average, than other derivative-free solvers in terms of solution quality within 2,500 function evaluations.
Journal ArticleDOI
ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations
TL;DR: The purpose of this paper is to show how the extensible structure of ANTIGONE realizes the authors' previously-proposed mixed- integer quadratically-constrained quadratic program and mixed-integer signomial optimization computational frameworks.
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A review of recent advances in global optimization
TL;DR: This paper presents an overview of the research progress in deterministic global optimization during the last decade (1998-2008).
Book
Evaluation and Decision Models: A Critical Perspective
TL;DR: This chapter discusses the process of building and aggregating evaluations for decision-making on the basis of several opinions and the challenges of dealing with uncertainty.
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On the assessment of robustness
TL;DR: In this article, a framework for assessing robustness is proposed, taking basis in decision analysis theory, by computing both direct risk associated with the direct consequences of potential damages to the system, and indirect risk, which corresponds to the increased risk of a damaged system.
References
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Book
Iterative Solution of Nonlinear Equations in Several Variables
J.M. Ortega,Werner C. Rheinboldt +1 more
TL;DR: In this article, the authors present a list of basic reference books for convergence of Minimization Methods in linear algebra and linear algebra with a focus on convergence under partial ordering.
Journal ArticleDOI
An efficient method for finding the minimum of a function of several variables without calculating derivatives
Book
An introduction to variational inequalities and their applications
TL;DR: In this paper, the SIAM edition Preface Glossary of notations Introduction Part I. Variational Inequalities in Rn Part II. Free Boundary Problems Governed by Elliptic Equations and Systems Part VII. A One Phase Stefan Problem Bibliography Index.
Journal ArticleDOI
Conditioning of Quasi-Newton Methods for Function Minimization
TL;DR: In this paper, a class of approximating matrices as a function of a scalar parameter is presented, where the problem of optimal conditioning of these matrices under an appropriate norm is investigated and a set of computational results verifies the superiority of the new methods arising from conditioning considerations to known methods.