By Singiresu S Rao
Helps you progress from idea to optimizing engineering platforms in virtually any
Now in its Fourth version, Professor Singiresu Rao's acclaimed textual content Engineering Optimization allows readers to quick grasp and practice all of the very important optimization equipment in use this day throughout a wide variety of industries. overlaying either the most recent and classical optimization equipment, the textual content starts with the fundamentals after which gradually builds to complex ideas and functions.
This entire textual content covers nonlinear, linear, geometric, dynamic, and stochastic programming ideas in addition to extra really expert tools reminiscent of multiobjective, genetic algorithms, simulated annealing, neural networks, particle swarm optimization, ant colony optimization, and fuzzy optimization. each one technique is gifted in transparent, elementary language, making even the extra refined ideas effortless to understand. additionally, the writer presents:
Case examples that exhibit how each one approach is utilized to resolve real-world difficulties throughout numerous industries
Review questions and difficulties on the finish of every bankruptcy to interact readers in utilising their newfound abilities and knowledge
Examples that show using MATLAB® for the answer of other different types of sensible optimization problems
References and bibliography on the finish of every bankruptcy for exploring themes in larger depth
Answers to check Questions to be had at the author's site to assist readers to check their realizing of the fundamental concepts
With its emphasis on problem-solving and functions, Engineering Optimization is perfect for upper-level undergraduates and graduate scholars in mechanical, civil, electric, chemical, and aerospace engineering. moreover, the textual content is helping practising engineers in nearly any layout superior, extra effective structures at much less cost.Content:
Chapter 1 advent to Optimization (pages 1–62):
Chapter 2 Classical Optimization ideas (pages 63–118):
Chapter three Linear Programming I: Simplex procedure (pages 119–176):
Chapter four Linear Programming II: extra issues and Extensions (pages 177–247):
Chapter five Nonlinear Programming I: One?Dimensional Minimization equipment (pages 248–300):
Chapter 6 Nonlinear Programming II: Unconstrained Optimization ideas (pages 301–379):
Chapter 7 Nonlinear Programming III: limited Optimization strategies (pages 380–491):
Chapter eight Geometric Programming (pages 492–543):
Chapter nine Dynamic Programming (pages 544–587):
Chapter 10 Integer Programming (pages 588–631):
Chapter eleven Stochastic Programming (pages 632–667):
Chapter 12 optimum keep watch over and Optimality standards equipment (pages 668–692):
Chapter thirteen sleek tools of Optimization (pages 693–736):
Chapter 14 sensible facets of Optimization (pages 737–778):
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Additional info for Engineering Optimization: Theory and Practice, Fourth Edition
The modern methods of optimization, including genetic algorithms, simulated annealing, particle swarm optimization, ant colony optimization, neural network-based optimization, and fuzzy optimization, are presented in Chapter 13. Several practical aspects of optimization are outlined in Chapter 14. The reduction of size of optimization problems, fast reanalysis techniques, the efficient computation of the derivatives of static displacements and stresses, eigenvalues and eigenvectors, and transient response are outlined.
Arora, Applied Optimal Design: Mechanical and Structural Systems, Wiley, New York, 1979. E. Sevin and W. D. Pilkey, Optimum Shock and Vibration Isolation, Shock and Vibration Information Center, Washington, DC, 1971. 32 J. , Academic Press, San Diego, 2004. P. Y. Papalambros and D. J. Wilde, Principles of Optimal Design, Cambridge University Press, Cambridge, UK, 1988. J. N. Siddall, Optimal Engineering Design: Principles and Applications, Marcel Dekker, New York, 1982. S. S. , Wiley, New York, 1984.
Zangwill, Nonlinear Programming: A Unified Approach, Prentice-Hall, Englewood Cliffs, NJ, 1969. J. E. Dennis and R. B. Schnabel, Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Prentice-Hall, Englewood Cliffs, NJ, 1983. J. S. Kowalik, Methods for Unconstrained Optimization Problems, American Elsevier, New York, 1968. A. V. Fiacco and G. P. McCormick, Nonlinear Programming: Sequential Unconstrained Minimization Techniques, Wiley, New York, 1968. G. Zoutendijk, Methods of Feasible Directions, Elsevier, Amsterdam, 1960.