Engineering Optimization: A Modern Approach

Ranjan Ganguli

ISBN: 9788173717390 | Year: 2011 | Paperback | Pages: 268 | Language : English

Book Size: 180 x 240 mm | Territorial Rights: Restricted

Price: 870.00

About the Book

The deployment of optimization techniques at the conceptual design stage of complex technical systems is today no longer a desirable trait but an absolute necessity. This book aims to make the optimization technique pervasive in engineering design by moving the problem from an academic setting to an industrial platform. It provides a thorough understanding of the concepts of optimization necessary for a robust design of technical systems. The approach is from a modern perspective—it dwells on surrogate modelling and non-gradient-based algorithms and at the same time emphasizes classical methods for pedagogical reasons. Nonlinear optimization, response-surface method and genetic-algorithm approaches have been focussed upon to bridge the gap between nonlinear  programming and engineering optimization techniques.
The best way to learn optimization methods is undoubtedly by solving problems and following it up with exercises in computer programming. To enable this experience, the book has several solved examples, some of them non-trivial, besides many unsolved problems for the student to work out.

Contributors (Author(s), Editor(s), Translator(s), Illustrator(s) etc.)

Ranjan Ganguli is a professor in the Department of Aerospace Engineering at the Indian Institute of Science Bangalore. He received his PhD and MS degrees from the Department of Aerospace Engineering, University of Maryland, USA, and his BTech (Honors) degree from IIT Kharagpur. Dr Ganguli works in the area of design optimization, structural dynamics and aeroelasticity. He is an associate fellow of the American Institute of Aeronautics and Astronautics and a fellow of the Indian National Academy of Engineering.

Table of Content

Preface

Chapter 1 : Basic Concepts
Chapter 2 : Direct One-Dimensional Search
Chapter 3 : Gradient-Based Methods
Chapter 4 : Newtonian Methods
Chapter 5 : Constrained Optimization Methods
Chapter 6 : Response Surface Method
Chapter 7 : Genetic Algorithm

Bibliography
Index

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