Engineering Optimization: Theory And Practice - 5th Edition
Singiresu S. Rao
Venduto da Basi6 International, Irving, TX, U.S.A.
Venditore AbeBooks dal 24 giugno 2016
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Aggiungere al carrelloVenduto da Basi6 International, Irving, TX, U.S.A.
Venditore AbeBooks dal 24 giugno 2016
Condizione: Nuovo
Quantità: 1 disponibili
Aggiungere al carrelloNew. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Codice articolo ABEOCT25-144401
The revised and updated new edition of the popular optimization book for engineers
The thoroughly revised and updated fifth edition of Engineering Optimization: Theory and Practice offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The author—a noted expert on the topic—presents both the classical and most recent optimizations approaches. The book introduces the basic methods and includes information on more advanced principles and applications.
The fifth edition presents four new chapters: Solution of Optimization Problems Using MATLAB; Metaheuristic Optimization Methods; Multi-Objective Optimization Methods; and Practical Implementation of Optimization. All of the book's topics are designed to be self-contained units with the concepts described in detail with derivations presented. The author puts the emphasis on computational aspects of optimization and includes design examples and problems representing different areas of engineering. Comprehensive in scope, the book contains solved examples, review questions and problems. This important book:
Written for students across all engineering disciplines, the revised edition of Engineering Optimization: Theory and Practice is the comprehensive book that covers the new and recent methods of optimization and reviews the principles and applications.
Singiresu S. Rao is a Professor in the Mechanical and Aerospace Engineering Department at the University of Miami. His main areas of research include multi objective optimization and uncertainty models in engineering analysis, design and optimization.
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