Discrete Geometry and Optimization

Inbunden, Engelska, 2013

Del i serien Fields Institute Communications

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Beskrivning

?Optimization has long been a source of both inspiration and applications for geometers, and conversely, discrete and convex geometry have provided the foundations for many optimization techniques, leading to a rich interplay between these subjects.

Produktinformation

Utgivningsdatum:2013-07-19
Mått:155 x 235 x 24 mm
Vikt:658 g
Format:Inbunden
Språk:Engelska
Serie:Fields Institute Communications
Antal sidor:336
Upplaga:2013
Förlag:Springer International Publishing AG
ISBN:9783319001999

Utforska kategorier

Optimering inom Naturvetenskap och teknik
Matematik inom Naturvetenskap och teknik

Innehållsförteckning

Preface.- Discrete Geometry in Minkowski Spaces (Alonso, Martini, and Spirova).- Engineering Branch-and-Cut Algorithms for the Equicut Program (Anjos, Liers, Pardella, and Schmutzer).- An Approach to the Dodecahedral Conjecture Based on Bounds for Spherical Codes (Anstreicher).- On Minimal Tilings with Convex Cells Each Containing a Unit Ball (Bezdek).- On Volumes of Permutation Polytopes (Burggraf, De Loera, and Omar).- Monotone Paths in Planar Convex Subdivisions and Polytopes (Dumitrescu, Rote, and Toth).- Complexity of the Positive Semidefinite Matrix Completion Problem with a Rank Constraint (Eisenberg-Nagy, Laurent, and Varvitsiotis).- The Strong Dodecahedral Conjecture and Fejes Toth's Conjecture on Sphere Packings with Kissing Number Twelve (Hales).- Solving Nuclear Norm Regularized and Semidefinite Matrix Least Squares Problems with Linear Equality Constraints (Jiang, Sun, and Toh).- Techniques for Submodular Maximization (Lee).- A Further Generalization of the Colourful Caratheodory theorem (Meunier, Deza).- Expected Crossing Numbers (Mohar, Stephen).- EL-Labelings and Canonical Spanning Trees for Subword Complexes (Pilaud, Stump).- Bandwidth, Vertex Separators, and Eigenvalue Optimization (Rendl, Lisser, and Piacentini).- Exploiting Symmetries in Polyhedral Computations (Schurmann).- Conditions for Correct Sensor Network Localization Using SDP Relaxation (Shamsi, Taheri, Zhu, and Ye).- A Primal-Dual Smooth Perceptron-von Neumann Algorithm (Soheili, Pena).- Open Problems (Bezdek, Deza, and Ye).