Giuseppe C. Calafiore

Optimization Models (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Emphasizing practical understanding over the technicalities of specific algorithms, this elegant textbook is an accessible introduction to the field of optimization, focusing on powerful and reliable convex optimization techniques. Students and practitioners will learn how to recognize, simplify, model and solve optimization problems - and apply these principles to their own projects. A clear and self-contained introduction to linear algebra demonstrates core mathematical concepts in a way that is easy to follow, and helps students to understand their practical relevance. Requiring only a basic understanding of geometry, calculus, probability and statistics, and striking a careful balance between accessibility and rigor, it enables students to quickly understand the material, without being overwhelmed by complex mathematics. Accompanied by numerous end-of-chapter problems, an online solutions manual for instructors, and relevant examples from diverse fields including engineering, data science, economics, finance, and management, this is the perfect introduction to optimization for undergraduate and graduate students.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 31. Oktober 2014
• Englisch
• ISBN-13: 9781139986007
• Artikelnr.: 49268069

Autorenporträt

Giuseppe C. Calafiore is an Associate Professor at the Dipartimento di Automatica e Informatica, Politecnico di Torino, and a Research Fellow of the Institute of Electronics, Computer and Telecommunication Engineering, National Research Council of Italy.

Inhaltsangabe

1. Introduction
Part I. Linear Algebra: 2. Vectors
3. Matrices
4. Symmetric matrices
5. Singular value decomposition
6. Linear equations and least-squares
7. Matrix algorithms
Part II. Convex Optimization: 8. Convexity
9. Linear, quadratic and geometric models
10. Second-order cone and robust models
11. Semidefinite models
12. Introduction to algorithms
Part III. Applications: 13. Learning from data
14. Computational finance
15. Control problems
16. Engineering design.