Handbook on Semidefinite, Conic and Polynomial Optimization

Edited by Miguel F. Anjos () and Jean B. Lasserre ()

in International Series in Operations Research and Management Science from Springer, currently edited by Camille C. Price, Joe Zhu and Frederick S. Hillier

Date: 2012
ISBN: 978-1-4614-0769-0
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Chapters in this book:

Ch Chapter 1 Introduction to Semidefinite, Conic and Polynomial Optimization

Miguel F. Anjos and Jean B. Lasserre

Ch Chapter 10 A “Joint+Marginal” Approach in Optimization

Jean B. Lasserre

Ch Chapter 11 An Introduction to Formally Real Jordan Algebras and Their Applications in Optimization

F. Alizadeh

Ch Chapter 12 Complementarity Problems Over Symmetric Cones: A Survey of Recent Developments in Several Aspects

Akiko Yoshise

Ch Chapter 13 Convexity and Semidefinite Programming in Dimension-Free Matrix Unknowns

J. William Helton, Igor Klep and Scott McCullough

Ch Chapter 14 Positivity and Optimization: Beyond Polynomials

Jean B. Lasserre and Mihai Putinar

Ch Chapter 15 Self-Regular Interior-Point Methods for Semidefinite Optimization

Maziar Salahi and Tamás Terlaky

Ch Chapter 16 Elementary Optimality Conditions for Nonlinear SDPs

Florian Jarre

Ch Chapter 17 Recent Progress in Interior-Point Methods: Cutting-Plane Algorithms and Warm Starts

Alexander Engau

Ch Chapter 18 Exploiting Sparsity in SDP Relaxation of Polynomial Optimization Problems

Sunyoung Kim and Masakazu Kojima

Ch Chapter 19 Block Coordinate Descent Methods for Semidefinite Programming

Zaiwen Wen, Donald Goldfarb and Katya Scheinberg

Ch Chapter 2 The Approach of Moments for Polynomial Equations

Monique Laurent and Philipp Rostalski

Ch Chapter 20 Projection Methods in Conic Optimization

Didier Henrion and Jérôme Malick

Ch Chapter 21 SDP Relaxations for Non-Commutative Polynomial Optimization

Miguel Navascués, Stefano Pironio and Antonio Acín

Ch Chapter 22 Semidefinite Programming and Constraint Programming

Willem-Jan Hoeve

Ch Chapter 23 The State-of-the-Art in Conic Optimization Software

Hans D. Mittelmann

Ch Chapter 24 Latest Developments in the SDPA Family for Solving Large-Scale SDPs

Makoto Yamashita, Katsuki Fujisawa, Mituhiro Fukuda, Kazuhiro Kobayashi, Kazuhide Nakata and Maho Nakata

Ch Chapter 25 On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0

Kim-Chuan Toh, Michael Todd and Reha H. Tütüncü

Ch Chapter 26 PENNON: Software for Linear and Nonlinear Matrix Inequalities

Michal Kocvara and Michael Stingl

Ch Chapter 27 SDP Relaxations for Some Combinatorial Optimization Problems

Renata Sotirov

Ch Chapter 28 Computational Approaches to Max-Cut

Laura Palagi, Veronica Piccialli, Franz Rendl, Giovanni Rinaldi and Angelika Wiegele

Ch Chapter 29 Global Approaches for Facility Layout and VLSI Floorplanning

Miguel F. Anjos and Frauke Liers

Ch Chapter 3 Algebraic Degree in Semidefinite and Polynomial Optimization

Kristian Ranestad

Ch Chapter 30 Euclidean Distance Matrices and Applications

Nathan Krislock and Henry Wolkowicz

Ch Chapter 31 Sparse PCA: Convex Relaxations, Algorithms and Applications

Youwei Zhang, Alexandre d’Aspremont and Laurent El Ghaoui

Ch Chapter 4 Semidefinite Representation of Convex Sets and Convex Hulls

J. William Helton and Jiawang Nie

Ch Chapter 5 Convex Hulls of Algebraic Sets

João Gouveia and Rekha Thomas

Ch Chapter 6 Convex Relaxations and Integrality Gaps

Eden Chlamtac and Madhur Tulsiani

Ch Chapter 7 Relaxations of Combinatorial Problems Via Association Schemes

Etienne Klerk, Fernando M. Oliveira Filho and Dmitrii V. Pasechnik

Ch Chapter 8 Copositive Programming

Samuel Burer

Ch Chapter 9 Invariant Semidefinite Programs

Christine Bachoc, Dion C. Gijswijt, Alexander Schrijver and Frank Vallentin

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DOI: 10.1007/978-1-4614-0769-0

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