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The book begins with a review of basic definitions and notations and also provides the related fundamental background of linear algebra, geometry, and calculus. With this foundation, the authors explore the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. An optimization perspective on global search methods is featured and includes discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. In addition, the book includes an elementary introduction to artificial neural networks, convex optimization, and multiobjective optimization, all of which are of tremendous interest to students, researchers, and practitioners.
Additional features of the Third Edition include: New discussions of semidefinite programming and Lagrangian algorithms, A new chapter on global search methods, A new chapter on multiobjective optimization, New and modified examples and exercises in each chapter as well as an updated bibliography containing new references, An updated Instructor'sManual with fully worked-out solutions to the exercises.
Numerous diagrams and figures found throughout the text complement the written presentation of key concepts, and each chapter is followed by MATLAB exercises and drill problems that reinforce the discussed theory and algorithms. With innovative coverage and a straightforward approach, An Introduction to Optimization, Third Edition is an excellent book for courses in optimization theory and methods at the upper-undergraduate and graduate levels. It also serves as a useful, self-contained reference for researchers and professionals in a wide array of fields.
About the Author:
Edwin K.P. Chong, PhD, is Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University
About the Author:
Stanislaw H. Zak, PhD, is Professor of Electrical and Computer Engineering at Purdue University