Author |
: Jasbir Singh Arora |
Publisher |
: Elsevier |
Total Pages |
: 1121 |
Release |
: 2023-11-15 |
ISBN-10 |
: 9780128183212 |
ISBN-13 |
: 0128183217 |
Rating |
: 4/5 (12 Downloads) |
Book Synopsis Introduction to Optimum Design by : Jasbir Singh Arora
Download or read book Introduction to Optimum Design written by Jasbir Singh Arora and published by Elsevier. This book was released on 2023-11-15 with total page 1121 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Optimum Design, Fifth Edition is the most widely used textbook in engineering optimization and optimum design courses. It is intended for use in a first course on engineering design and optimization at the undergraduate or graduate level within engineering departments of all disciplines, but primarily within mechanical, aerospace and civil engineering. The basic approach of the text presents an organized approach to engineering design optimization in a rigorous yet simplified manner, illustrating various concepts and procedures with simple examples and demonstrating their applicability to engineering design problems. Formulation of a design problem as an optimization problem is emphasized and illustrated throughout the text. Excel and MATLAB are featured as learning and teaching aids. This new edition has been enhanced with new or expanded content in such areas as reliability-based optimization, metamodeling, design of experiments, robust design, nature-inspired metaheuristic search methods, and combinatorial optimizaton. - Describes basic concepts of optimality conditions and numerical methods with simple and practical examples, making the material highly teachable and learnable - Includes applications of optimization methods for structural, mechanical, aerospace, and industrial engineering problems - Covers practical design examples and introduces students to the use of optimization methods - Serves the needs of instructors who teach more advanced courses - Features new or expanded contents in such areas as design under uncertainty - reliability-based design optimization, metamodeling - response surface method, design of experiments, nature-inspired metaheuristic search methods, and robust design