INTRODUCTION TO LINEAR OPTIMIZATION
1143430617
The book presents a graduate level, rigorous, and self-contained introduction to linear optimization (LO), the presented topics being
Contents:
- Preface
- About the Author
- Main Notational Conventions
- Introduction to LO: Examples of LO Models
- Geometry of Linear Optimization:
- Polyhedral Sets and their Geometry
- Theory of Systems of Linear Inequalities and Duality
- Classical Algorithms of Linear Optimization: The Simplex Method:
- Simplex Method
- The Network Simplex Algorithm
- Complexity of Linear Optimization and the Ellipsoid Method:
- Polynomial Time Solvability of Linear Optimization
- Conic Programming and Interior Point Methods:
- Conic Programming
- Interior Point Methods for LO and Semidefinite Optimization
- Appendices:
- Prerequisites from Linear Algebra
- Prerequisites from Real Analysis
- Symmetric Matrices
- Bibliography
- Solutions to Selected Exercises
- Index
Readership: Senior undergraduate and graduate students dealing with building and processing optimizaiton models. Main textbook for a semester-long graduate course on linear optimization; auxiliary text for more general graduate courses on optimization.
Key Features:
- Linear optimization has wide application in decision making, engineering, and data science
- The author is a renowned expert on the topic
- Self-contained with background information summarized in the appendices
- Rigorous presentation of all the essential but avoid heavy technical detail wherever possible
- Novel approach or results: (1) presenting "calculus" of problems reducible to LO (something which traditionally is taught via a sample of instructive examples) including, in particular, the results on polynomial time reducibility of Conic Quadratic Optimization to LO; (2) Another novelty is in presenting the basic theory of contemporary extension of LO — Conic Programming, primarily, Conic Quadratic and Semidefinite Optimization, with emphasis on expressive abilities of these generic problems and on Conic Programming Duality; (3) In addition, we describe basic versions of polynomial time primal-dual path-following algorithms for LO and SDO and carry out rigorous complexity analysis of these algorithms
INTRODUCTION TO LINEAR OPTIMIZATION
The book presents a graduate level, rigorous, and self-contained introduction to linear optimization (LO), the presented topics being
Contents:
- Preface
- About the Author
- Main Notational Conventions
- Introduction to LO: Examples of LO Models
- Geometry of Linear Optimization:
- Polyhedral Sets and their Geometry
- Theory of Systems of Linear Inequalities and Duality
- Classical Algorithms of Linear Optimization: The Simplex Method:
- Simplex Method
- The Network Simplex Algorithm
- Complexity of Linear Optimization and the Ellipsoid Method:
- Polynomial Time Solvability of Linear Optimization
- Conic Programming and Interior Point Methods:
- Conic Programming
- Interior Point Methods for LO and Semidefinite Optimization
- Appendices:
- Prerequisites from Linear Algebra
- Prerequisites from Real Analysis
- Symmetric Matrices
- Bibliography
- Solutions to Selected Exercises
- Index
Readership: Senior undergraduate and graduate students dealing with building and processing optimizaiton models. Main textbook for a semester-long graduate course on linear optimization; auxiliary text for more general graduate courses on optimization.
Key Features:
- Linear optimization has wide application in decision making, engineering, and data science
- The author is a renowned expert on the topic
- Self-contained with background information summarized in the appendices
- Rigorous presentation of all the essential but avoid heavy technical detail wherever possible
- Novel approach or results: (1) presenting "calculus" of problems reducible to LO (something which traditionally is taught via a sample of instructive examples) including, in particular, the results on polynomial time reducibility of Conic Quadratic Optimization to LO; (2) Another novelty is in presenting the basic theory of contemporary extension of LO — Conic Programming, primarily, Conic Quadratic and Semidefinite Optimization, with emphasis on expressive abilities of these generic problems and on Conic Programming Duality; (3) In addition, we describe basic versions of polynomial time primal-dual path-following algorithms for LO and SDO and carry out rigorous complexity analysis of these algorithms
62.0
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INTRODUCTION TO LINEAR OPTIMIZATION
648
INTRODUCTION TO LINEAR OPTIMIZATION
648
62.0
In Stock
Product Details
| ISBN-13: | 9789811277924 |
|---|---|
| Publisher: | WSPC |
| Publication date: | 01/25/2024 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| Pages: | 648 |
| File size: | 39 MB |
| Note: | This product may take a few minutes to download. |
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