Optimization For Engineering Design Algorithms And Examples

Optimization For Engineering Design Algorithms And Examples

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Product Specifications

Publisher PHI Learning All Mathematics books by PHI Learning
ISBN 9788120346789
Author: Deb And Kalyanmoy
Number of Pages 441
Available
Available in all digital devices
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Optimization For Engineering Design Algorithms And Examples by Deb And Kalyanmoy
Book Summary:
This well-received book, now in its second edition, continues to provide a number of optimization algorithms which are commonly used in computer-aided engineering design. The book begins with simple single-variable optimization techniques, and then goes on to give unconstrained and constrained optimization techniques in a step-by-step format so that they can be coded in any user-specific computer language. In addition to classical optimization methods, the book also discusses Genetic Algorithms and Simulated Annealing, which are widely used in engineering design problems because of their ability to find global optimum solutions.

Audience of the Book :

The book is suitable for senior undergraduate/postgraduate students of mechanical, production and chemical engineering. Students in other branches of engineering offering optimization courses as well as designers and decision-makers will also find the book useful.

This book is recommended in NIT Agartala, Tripura, Assam Engineering College, Assam, IIT Guwuhati, Asssam and NIT Silchar, Assam.

 
Key Features:

The main features of the book are as follows:

 • Algorithms are presented in a step-by-step format to facilitate coding in a computer language.
 • Sample computer programs in FORTRAN are appended for better comprehension.
 • Worked-out examples are illustrated for easy understanding.
 • The same example problems are solved with most algorithms for a comparative evaluation of the algorithms.
 

Table of Contents:
 • Introduction
 • Single-variable Optimization Algorithms
 • Multivariable Optimization Algorithms
 • Constrained Optimization Algorithms
 • Specialized Algorithms
 • Nontraditional Optimization Algorithms