Linear and Nonlinear Optimization

Authors: Igor Griva – Stephen G. Nash – Ariela Sofer

Publisher: Universities Press

Contents:

Part I – Basics:  

1 Optimization Models

2 Fundamentals of Optimization

3 Representation of Linear Constraints

Part  II – Linear Programming

4 Geometry of Linear Programming

5 The Simplex Method

6 Duality and Sensitivity

7 Enhancements of the Simplex Method

8 Network Problems

9 Computational Complexity of Linear Programming

10 Interior-Point Methods for Linear Programming

Part III – Unconstrained Optimization

11 Basics of Unconstrained Optimization

12 Methods for Unconstrained Optimization

13 Low-Storage Methods for Unconstrained Problems

Part IV – Nonlinear Optimization: 

14 Optimality Conditions for Constrained Problems

15 Feasible-Point Methods

16 Penalty and Barrier Methods

Part V

Appendices: A Topics from Linear Algebra

Appendices: B Other Fundamentals

Appendices: C Software 

 

 

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