Engineering Optimization: Theory and Practice, 3rd Edition
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More About This Title Engineering Optimization: Theory and Practice, 3rd Edition
English
SINGIRESU S. RAO, PhD, is a professor in the School of Mechanical Engineering at Purdue University. He earned his doctorate from Case Western Reserve University and has extensive teaching and research experience at Purdue, San Diego State University, Indian Institute of Technology (Kanpur), and NASA Langley Research Center. Dr. Rao has published more than 125 technical papers in internationally reputed journals and more than 100 papers in conference proceedings in the areas of engineering optimization, reliability-based design, fuzzy systems, active control of structures, concurrent design, and vibration engineering. His previous books include Optimization: Theory and Applications, The Finite Element Method in Engineering, Mechanical Vibrations, and Reliability-Based Design. Dr. Rao has edited several conference proceedings and served as the Conference Chairman and Papers Review Chairman for the ASME Design Automation Committee and as an Associate Editor for the ASME Journal of Mechanisms, Transmissions, and Automation in Design. Currently, he is on the editorial boards of Engineering Optimization, Reliability Engineering & System Safety, and Microelectronics and Reliability.
English
Introduction to Optimization.
Classical Optimization Techniques.
Linear Programming I: Simplex Method.
Linear Programming II: Additional Topics and Extensions.
Nonlinear Programming I: One-Dimensional Minimization Methods.
Nonlinear Programming II: Unconstrained Optimization Techniques.
Nonlinear Programming III: Constrained Optimization Techniques.
Geometric Programming.
Dynamic Programming.
Integer Programming.
Stochastic Programming.
Further Topics in Optimization.
Practical Aspects of Optimization.
Appendices.
Answers to Selected Problems.
Index.
Classical Optimization Techniques.
Linear Programming I: Simplex Method.
Linear Programming II: Additional Topics and Extensions.
Nonlinear Programming I: One-Dimensional Minimization Methods.
Nonlinear Programming II: Unconstrained Optimization Techniques.
Nonlinear Programming III: Constrained Optimization Techniques.
Geometric Programming.
Dynamic Programming.
Integer Programming.
Stochastic Programming.
Further Topics in Optimization.
Practical Aspects of Optimization.
Appendices.
Answers to Selected Problems.
Index.
