Moment And Polynomial Optimization


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Moment and Polynomial Optimization


Moment and Polynomial Optimization

Author: Jiawang Nie

language: en

Publisher:

Release Date: 2023


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"An accurate and concise introduction to optimality certificates, nonnegativity certificates for polynomials, characterization of moments, representations for convex sets, and various Positivstellensatz"--

Moment and Polynomial Optimization


Moment and Polynomial Optimization

Author: Jiawang Nie

language: en

Publisher: SIAM

Release Date: 2023-06-15


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Moment and polynomial optimization is an active research field used to solve difficult questions in many areas, including global optimization, tensor computation, saddle points, Nash equilibrium, and bilevel programs, and it has many applications. The author synthesizes current research and applications, providing a systematic introduction to theory and methods, a comprehensive approach for extracting optimizers and solving truncated moment problems, and a creative methodology for using optimality conditions to construct tight Moment-SOS relaxations. This book is intended for applied mathematicians, engineers, and researchers entering the field. It can be used as a textbook for graduate students in courses on convex optimization, polynomial optimization, and matrix and tensor optimization.

Moments, Positive Polynomials and Their Applications


Moments, Positive Polynomials and Their Applications

Author: Jean-Bernard Lasserre

language: en

Publisher: World Scientific

Release Date: 2010


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Many important problems in global optimization, algebra, probability and statistics, applied mathematics, control theory, financial mathematics, inverse problems, etc. can be modeled as a particular instance of the Generalized Moment Problem (GMP). This book introduces, in a unified manual, a new general methodology to solve the GMP when its data are polynomials and basic semi-algebraic sets. This methodology combines semidefinite programming with recent results from real algebraic geometry to provide a hierarchy of semidefinite relaxations converging to the desired optimal value. Applied on appropriate cones, standard duality in convex optimization nicely expresses the duality between moments and positive polynomials. In the second part of this invaluable volume, the methodology is particularized and described in detail for various applications, including global optimization, probability, optimal context, mathematical finance, multivariate integration, etc., and examples are provided for each particular application.