Technology/Engineering/MechanicalHelps you move from theory to optimizing engineering systems in almost any industryNow 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 industriesReview questions and problems at the end of each chapter to engage readers in applying their newfound skills and knowledgeExamples that demonstrate the use of MATLABĀ® for the solution of different types of practical optimization problemsReferences and bibliography at the end of each chapter for exploring topics in greater depthAnswers to Review Questions available on the author's Web site to help readers to test their understanding of the basic conceptsWith its emphasis on problem-solving and applications, 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.
Author(s): Singiresu S. Rao
Edition: 4
Year: 2009
Language: English
Pages: 830
0470183527......Page 1
Engineering Optimization: Theory and Practice, Fourth Edition......Page 3
Contents......Page 6
Preface......Page 16
1
Introduction to Optimization......Page 19
2
Classical Optimization Techniques......Page 81
3
Linear Programming I:
Simplex Method......Page 137
4
Linear Programming II:
Additional Topics and Extensions......Page 195
5
Nonlinear Programming I:
One-Dimensional Minimization
Methods......Page 266
6
Nonlinear Programming II:
Unconstrained Optimization
Techniques......Page 319
7
Nonlinear Programming III:
Constrained Optimization
Techniques......Page 398
8
Geometric Programming......Page 510
9
Dynamic Programming......Page 562
10
Integer Programming......Page 606
11
Stochastic Programming......Page 650
12
Optimal Control and Optimality
Criteria Methods......Page 686
13
Modern Methods of Optimization......Page 711
14
Practical Aspects of Optimization......Page 755
A
Convex and Concave Functions......Page 797
B
Some Computational Aspects
of Optimization......Page 802
C
Introduction to MATLAB......Page 809
Answers to Selected Problems......Page 813
Index......Page 820