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
Note: Prices are subject to change
For orders write to:
garudalearning@gmail.com
gldatascience@gmail.com
₹1,295.00