Overview
A rigorous mathematical approach to identifying a set of design alternatives and selecting the best candidate from within that set, engineering optimization was developed as a means of helping engineers to design systems that are both more efficient and less expensive and to develop new ways of improving the performance of existing systems. Thanks to the breathtaking growth in computer technology that has occurred over the past decade, optimization techniques can now be used to find creative solutions to larger, more complex problems than ever before. As a consequence, optimization is now viewed as an indispensable tool of the trade for engineers working in many different industries, especially the aerospace, automotive, chemical, electrical, and manufacturing industries. In Engineering Optimization, Professor Singiresu S. Rao provides an application-oriented presentation of the full array of classical and newly developed optimization techniques now being used by engineers in a wide range of industries. Essential proofs and explanations of the various techniques are given in a straightforward, user-friendly manner, and each method is copiously illustrated with real-world examples that demonstrate how to maximize desired benefits while minimizing negative aspects of project design. Comprehensive, authoritative, up-to-date, Engineering Optimization provides in-depth coverage of linear and nonlinear programming, dynamic programming, integer programming, and stochastic programming techniques as well as several breakthrough methods, including genetic algorithms, simulated annealing, and neural network-based and fuzzy optimization techniques. Designed to function equally well as either a professional reference or a graduate-level text, Engineering Optimization features many solved problems taken from several engineering fields, as well as review questions, important figures, and helpful references. Engineering Optimization is a valuable working resource for engineersSynopsis
Technology/Engineering/Mechanical
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.
Booknews
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)