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Numerical Optimization with Applications
Author(s): Suresh Chandra, Jayadeva, Aparna Mehra

ISBN:    978-81-7319-854-0 
Publication Year:   Reprint 2013
Pages:   710
Binding:   Paper Back
Dimension:   185mm x 240mm
Weight:   1130


About the book

Numerical Optimization with Applications provides a focused and detailed study of various numerical optimization methods and their applications in Science, Engineering and Management. Apart from discussing standard optimization methods and their traditional applications, the book includes some very recent topics like Semi-definite Programming, Second Order Cone Programming, Evolutionary Methods and Global optimization. An attempt has been made to present some modern and non-conventional applications of numerical optimization in the areas of Machine Learning, VLSI Design/ Electrical Circuits and Financial Mathematics. A distinctive feature of the book is also to provide basic MATLAB codes as building blocks for readers to develop their own codes for various algorithms discussed in the book.

Key Features

  • • A class room teaching style of the presentation. • Non-conventional and Modern applications of numerical optimization in the areas of Machine Learning, VLSI Design/ Electrical Circuits and Financial Mathematics. • Basic MATLAB codes as building blocks for various algorithms. • A good collection of end chapters exercises some of which have been specifically constructed for the book. • Suitable as a textbook on optimization for M. Sc., B. Tech/ M. Tech as well as MBA students.

Table of Contents

Preface / Introduction / Linear Programming / Mathematics of the Simplex Method / Duality in Linear Programming / The Transportation and Assignment Problems / Integer Linear Programming / Convex Optimization and Quadratic Programming / Optimality Conditions and Duality in Nonlinear Programming / Unconstrained Optimization Problems / Algorithms in Nonlinear Programming / Computational Complexity and Karmarkar’s Algorithm for Linear Programming / Some Generalized Convex Functions and Fractional Programming / Multi-Objective Optimization: Theory and Methods / Semi-definite Programming / Evolutionary Methods and Global Optimization / Mathematical Programming Applications in Machine Learning / Mathematical Programming Applications in Financial Mathematics / Mathematical Programming Applications in Engineering / Matlab Codes for Some Selected Algorithms / References / Index.


Undergraduate and Postgraduate Students, Professionals & Researchers


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