By Singiresu S Rao
Helps you progress from thought to optimizing engineering structures in nearly any
Now in its Fourth variation, Professor Singiresu Rao's acclaimed textual content Engineering Optimization allows readers to fast grasp and follow all of the very important optimization tools in use this present day throughout a extensive variety of industries. masking either the newest and classical optimization tools, the textual content begins with the fundamentals after which gradually builds to complex ideas and purposes.
This entire textual content covers nonlinear, linear, geometric, dynamic, and stochastic programming thoughts in addition to extra really expert equipment corresponding to multiobjective, genetic algorithms, simulated annealing, neural networks, particle swarm optimization, ant colony optimization, and fuzzy optimization. each one approach is gifted in transparent, undemanding language, making even the extra refined concepts effortless to know. additionally, the writer offers:
Case examples that express how every one approach is utilized to unravel real-world difficulties throughout a number of industries
Review questions and difficulties on the finish of every bankruptcy to have interaction readers in utilizing their newfound abilities and knowledge
Examples that display using MATLAB® for the answer of alternative varieties of functional optimization problems
References and bibliography on the finish of every bankruptcy for exploring subject matters in higher depth
Answers to study Questions to be had at the author's site to aid readers to check their realizing of the elemental 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 working towards engineers in nearly any layout more desirable, extra effective structures at much less cost.Content:
Chapter 1 creation to Optimization (pages 1–62):
Chapter 2 Classical Optimization recommendations (pages 63–118):
Chapter three Linear Programming I: Simplex process (pages 119–176):
Chapter four Linear Programming II: extra themes and Extensions (pages 177–247):
Chapter five Nonlinear Programming I: One?Dimensional Minimization equipment (pages 248–300):
Chapter 6 Nonlinear Programming II: Unconstrained Optimization suggestions (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 regulate and Optimality standards equipment (pages 668–692):
Chapter thirteen smooth tools of Optimization (pages 693–736):
Chapter 14 functional facets of Optimization (pages 737–778):
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Extra info for Engineering Optimization: Theory and Practice, Fourth Edition
12s. If the maximum thrust that can be developed at point i either in the positive or negative direction is restricted to a value of Fi , formulate the problem of minimizing the total time of travel under the following assumptions: 1. The rocket travels against the gravitational force. 2. The mass of the rocket reduces in proportion to the distance traveled. 3. The air resistance is proportional to the velocity of the rocket. 9 17 Control points in the path of the rocket. SOLUTION Let points (or control points) on the path at which the thrusts of the rocket are changed be numbered as 1, 2, 3, .
6 Classification Based on the Deterministic Nature of the Variables Based on the deterministic nature of the variables involved, optimization problems can be classified as deterministic and stochastic programming problems. Stochastic Programming Problem. A stochastic programming problem is an optimization problem in which some or all of the parameters (design variables and/or preassigned parameters) are probabilistic (nondeterministic or stochastic). 7 are deterministic programming problems. 95.
36 Introduction to Optimization The most widely circulated journals that publish papers related to engineering optimization are Engineering Optimization, ASME Journal of Mechanical Design, AIAA Journal, ASCE Journal of Structural Engineering, Computers and Structures, International Journal for Numerical Methods in Engineering, Structural Optimization, Journal of Optimization Theory and Applications, Computers and Operations Research, Operations Research, Management Science, Evolutionary Computation, IEEE Transactions on Evolutionary Computation, European Journal of Operations Research, IEEE Transactions on Systems, Man and Cybernetics, and Journal of Heuristics.