OPTIMIZATION FOR ENGINEERING DESIGN: Algorithms and Examples, Edition 2

KALYANMOY DEB

Nov 2012 · PHI Learning Pvt. Ltd.

About this ebook

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. The second edition adds several new topics of optimization such as design and manufacturing, data fitting and regression, inverse problems, scheduling and routing, data mining, intelligent system design, Lagrangian duality theory, and quadratic programming and its extension to sequential quadratic programming. It also extensively revises the linear programming algorithms section in the Appendix. This edition also includes more number of exercise problems. 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. Key Features 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.

About the author

KALYANMOY DEB, PhD (Alabama), Department of Mechanical Engineering, Indian Institute of Technology Kanpur, is a leading researcher in the area of evolutionary computation, particularly in the area of evolutionary multi-objective optimization (EMO). He has made seminal contributions in the development of evolutionary optimization algorithms including constraint handling, real-valued optimization, multi-objective optimization, dynamic optimization, uncertainty-based optimization, and others. His NSGA-II algorithm for multi-objective optimization is extremely popular and has been adopted in many commercial software programs on optimization. He has more than 300 publications in various national and international journals and conferences. Dr. Deb is in the editorial board of 18 international journals. He is the recipient of coveted Shanti Swarup Bhatnagar Prize in Engineering Sciences and the prestigious Infosys Prize.