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Algorithmic Principles of Mathematical Programming
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Real Vector Spaces
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Chapter 2
Linear Equations and Linear Inequalities
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Chapter 3
Polyhedra
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Chapter 4
Linear Programs and the Simplex Method
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Chapter 5
Lagrangian Duality
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Chapter 6
An Interior Point Algorithm for Linear Programs
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Chapter 7
Network Flows
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Chapter 8
Complexity
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Chapter 9
Integer Programming
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Chapter 10
Convex Sets and Convex Functions
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Chapter 11
Unconstrained Optimization
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Chapter 12
Constrained Nonlinear Optimization
Overall attention for this book and its chapters
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Mentioned by
twitter
1
X user
syllabi
2
institutions with syllabi
Citations
dimensions_citation
47
Dimensions
Readers on
mendeley
15
Mendeley
Book overview
1. Real Vector Spaces
2. Linear Equations and Linear Inequalities
3. Polyhedra
4. Linear Programs and the Simplex Method
5. Lagrangian Duality
6. An Interior Point Algorithm for Linear Programs
7. Network Flows
8. Complexity
9. Integer Programming
10. Convex Sets and Convex Functions
11. Unconstrained Optimization
12. Constrained Nonlinear Optimization
Summary
X
Syllabi
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
3
syllabi from
2
institutions on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
Indian Institute of Technology, Guwahati
1
Medicine
Unknown
2
Medicine