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Fundamentals Of Optimization : Methods, Minimum Principles, And Applications For Making Things Better

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1. Optimization : The Big Idea
1.1 Design Space
1.2 What Optimum?

2. Getting Started Optimization: Problem of a Single Variable
2.1 The Lifeguard Problem
2.2 Maximum Range
2.3 Maximum Electrical Power
2.4 Shortest Path for a Toy Car
2.5 Weight Snap-Through Spring
2.6 Solution Methods
2.7 Finding Roots Using Minimization
2.8 Optimizing Process: Ocean Shipping Routes.
2.9 MATLAB Examples

3. Minimum Principles: Optimization in the Fabric of the Universe
3.1 Evolution
3.2 Minimum Energy Structures
3.3 Optics: Fermat's Principle Snell's Laws.
3.4 General Relativity

4. Problems with More than One Variable
4.1 Two-Variable Lifeguard Problem
4.2 Least Squares Curve Fitting
4.3 Two-Variable Soap Film Problem
4.4 Solution Methods
4.5 Approximate Solution to a Differential Equation
4.6 Evolution-Inspired Semi-Random Search: Following Nature's Lead
4.7 Convex Problems
4.8 Optimization at the Limits: Unlimited Class Air Racers

5. Constraints: Placing Limits on the Solution
5.1 Maximum Volume of a Box
5.2 Constrained Lifeguard Problem: Exterior Penalty Function
5.3 Minimum Surface Area of a Can
5.4 Equality Constraints
5.5 Approximate Solutions

6. General Conditions for Solving Optimization Problems: Karush-Kuhn-Tucker Conditions
6.1 General Form of KKT Conditions
6.2 Application to an Unconstrained Problem of One Variable
6.3 Application to an Unconstrained Problem of Two Variables
6.4 Application to a Single Variable Problem with an Equality Constraint
6.5 Application to a Multivariable Problem with Inequality Constraints
6.6 Multiple Constraints. References

7. Discrete Variables
7.1 The Traveling Salesman Problem
7.2 Nearest Neighbor Algorithm
7.3 Applications of the Traveling Salesman Problem
7.4 Discrete Variable Problems
7.5 Examples of Discrete Variable Design Problems.

8. Aerospace Applications
8.1 Monoplane or Biplane
8.2 Wing Planforms
8.3 Vehicle Performance
8.4 Aircraft Design Optimization

9. Structural Optimization
9.1 Truss Structures
9.2 Updating Finite Element Models
9.3 Aeroelastically Scaled Wind Tunnel Model Design

10. Multiobjective Optimization
10.1 The Need for Multiobjective Optimization
10.2 A Simple Multiobjective Problem
10.3 Weighted Objectives Method
10.4 Hierarchical Optimization Method
10.5 Global Criterion Method
10.6 Pareto Optimality
10.7 A Multiobjective Inverse Spectral Problem
10.8 A Complex Multiobjective Design Problem

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

658.5 MAR f

Penerbit

Amerika : Springer., 2018

Deskripsi Fisik

xiii, 245 hlm. ; 24 cm

Bahasa

English

ISBN/ISSN

9783319761916

Klasifikasi

658.5

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Tipe Pembawa

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