Principles of Optimal Design: Modeling and ComputationCambridge University Press, 10.07.2000 - 390 Seiten Principles of Optimal Design puts the concept of optimal design on a rigorous foundation and demonstrates the intimate relationship between the mathematical model that describes a design and the solution methods that optimize it. Since the first edition was published, computers have become ever more powerful, design engineers are tackling more complex systems, and the term optimization is now routinely used to denote a design process with increased speed and quality. This second edition takes account of these developments and brings the original text thoroughly up to date. The book now includes a discussion of trust region and convex approximation algorithms. A new chapter focuses on how to construct optimal design models. Three new case studies illustrate the creation of optimization models. The final chapter on optimization practice has been expanded to include computation of derivatives, interpretation of algorithmic results, and selection of algorithms and software. Both students and practising engineers will find this book a valuable resource for design project work. |
Inhalt
Optimization Models | 1 |
12 Design Optimization | 10 |
13 Feasibility and Boundedness | 23 |
14 Topography of the Design Space | 30 |
15 Modeling and Computation | 38 |
16 Design Projects | 39 |
Model Construction | 44 |
22 Best Fit Curves and Least Squares | 49 |
55 Feasible Iterations | 186 |
56 Inequality Constraints | 194 |
57 Geometry of Boundary Optima | 198 |
58 Linear Programming | 203 |
59 Sensitivity | 214 |
510 Summary | 216 |
Parametric and Discrete Optima | 223 |
61 Parametric Solution | 224 |
23 Neural Networks | 51 |
24 Kriging | 54 |
25 Modeling a Drive Screw Linear Actuator | 57 |
26 Modeling an Internal Combustion Engine | 62 |
27 Design of a Geartrain | 71 |
28 Modeling Considerations Prior to Computation | 79 |
29 Summary | 83 |
Model Boundedness | 87 |
32 Constrained Optimum | 92 |
33 Underconstrained Models | 98 |
34 Recognizing Monotonicity | 103 |
35 Inequalities | 105 |
36 Equality Constraints | 109 |
37 Variables not in the Objects | 114 |
38 Nonmonotonic Functions | 116 |
39 Model Preparation Procedure | 119 |
310 Summary | 121 |
Interior Optima | 128 |
41 Existence | 129 |
42 Local Approximation | 131 |
43 Optimality | 137 |
44 Convexity | 143 |
45 Local Exploration | 149 |
46 Searching along a Line | 154 |
47 Stabilization | 157 |
48 Trust Regions | 160 |
49 Summary | 163 |
Boundary Optima | 168 |
52 Describing the Constraint Surface | 171 |
53 Equality Constraints | 174 |
54 Curvature at the Boundary | 180 |
62 The Monotonicity Table | 232 |
63 Functional Monotonicity Analysis | 240 |
64 Discrete Variables | 245 |
65 Discrete Design Activity and Optimality | 247 |
66 Transformer Design | 255 |
67 Constraint Derivation | 259 |
68 Relaxation and Exhaustive Enumeration | 270 |
69 Summary | 272 |
Local Computation | 278 |
71 Numerical Algorithms | 279 |
72 Single Variable Minimization | 285 |
73 QuasiNewton Methods | 296 |
74 Active Set Strategies | 300 |
75 Moving along the Boundary | 305 |
76 Penalties and Barriers | 306 |
77 Sequential Quadratic Programming | 313 |
79 Convex Approximation Algorithms | 324 |
710 Summary | 329 |
Principles and Practice | 337 |
81 Preparing Models for Numerical Computation | 338 |
82 Computing Derivatives | 342 |
83 Scaling | 348 |
84 Interpreting Numerical Results | 352 |
85 Selecting Algorithms and Software | 354 |
86 Optimization Checklist | 358 |
87 Concepts and Principles | 362 |
88 Summary | 366 |
| 369 | |
| 381 | |
| 385 | |
Andere Ausgaben - Alle anzeigen
Principles of Optimal Design: Modeling and Computation Panos Y. Papalambros,Douglass J. Wilde Keine Leseprobe verfügbar - 2000 |
Häufige Begriffe und Wortgruppen
active constraints active set strategy air tank algebraic algorithm approximation calculated Chapter computation Consider constraint activity constraint functions convergence convex convex set cylinder d₁ decreasing defined definition deleted derivative design model design optimization design problems design variables differential direction discrete eliminated engineering equality constraints Equation example feasible domain Figure finite function f global global optimization h₁ Hessian Hessian matrix inequality constraints infeasible infimum iteration K₁ KKT conditions Lagrange multipliers Lagrangian line search linear linear programming local minima lower bound matrix maximum metamodels minimize minimum monotonicity analysis Monotonicity Principle Newton's method null form objective function optimal design optimization model optimization problem optimum polynomial positive positive-definite procedure programming quadratic quasi-Newton methods reduced relaxed satisfied Section semiactive set constraint solution solving stationary point step stress subject to g₁ subproblem tangent Theorem transformation trust region unconstrained update vector x₁ xk+1 zero
Verweise auf dieses Buch
Thermal Design and Optimization Adrian Bejan,George Tsatsaronis,Michael J. Moran Eingeschränkte Leseprobe - 1995 |

