Helps you move from theory to optimizing engineering systems in almost any industry
Now in its Fourth Edition, Professor Singiresu Rao's acclaimed text Engineering Optimization enables readers to quickly master and apply all the important optimization methods in use today across a broad range of industries. Covering both the latest and classical optimization methods, the text starts off with the basics and then progressively builds to advanced principles and applications.
This comprehensive text covers nonlinear, linear, geometric, dynamic, and stochastic programming techniques as well as more specialized methods such as multiobjective, genetic algorithms, simulated annealing, neural networks, particle swarm optimization, ant colony optimization, and fuzzy optimization. Each method is presented in clear, straightforward language, making even the more sophisticated techniques easy to grasp. Moreover, the author provides:
Case examples that show how each method is applied to solve real-world problems across a variety of industries
Review questions and problems at the end of each chapter to engage readers in applying their newfound skills and knowledge
Examples that demonstrate the use of MATLAB® for the solution of different types of practical optimization problems
References and bibliography at the end of each chapter for exploring topics in greater depth
Answers to Review Questions available on the author's Web site to help readers to test their understanding of the basic concepts
With its emphasis on problem-solving andapplications, Engineering Optimization is ideal for upper-level undergraduates and graduate students in mechanical, civil, electrical, chemical, and aerospace engineering. In addition, the text helps practicing engineers in almost any industry design improved, more efficient systems at less cost.
A comprehensive professional reference or graduate-level textbook, presenting the theory, techniques, and applications of engineering optimization. Essential proofs and explanations of the various techniques are presented in a simple manner, and new concepts are illustrated with numerical examples. The coverage includes linear and nonlinear programming, integer programming, and stochastic programming techniques, as well as some recently developed methods such as genetic algorithms, simulated annealing, neural-network-based methods, and fuzzy optimization. Includes a large number of solved examples and review questions. Annotation c. Book News, Inc., Portland, OR (booknews.com)