Numerical Optimization

Portada
Springer Science & Business Media, 28 abr 2000 - 636 páginas
This is a book for people interested in solving optimization problems. Because of the wide (and growing) use of optimization in science, engineering, economics, and industry, it is essential for students and practitioners alike to develop an understanding of optimization algorithms. Knowledge of the capabilities and limitations of these algorithms leads to a better understanding of their impact on various applications, and points the way to future research on improving and extending optimization algorithms and software. Our goal in this book is to give a comprehensive description of the most powerful, state-of-the-art, techniques for solving continuous optimization problems. By presenting the motivating ideas for each algorithm, we try to stimulate the reader’s intuition and make the technical details easier to follow. Formal mathematical requirements are kept to a minimum. Because of our focus on continuous problems, we have omitted discussion of important optimization topics such as discrete and stochastic optimization.
 

Índice

Fundamentals of Unconstrained Optimization
11
InteriorPoint Methods
14
3
30
4
55
Notes and References
61
3
87
Conjugate Gradient Methods
102
Notes and References
124
Notes and References
356
5
374
Pricing and Selection of the Entering Index
381
2
401
3
407
Notes and References
414
Notes and References
436
6
474

3
142
Gershgorin Modification
150
Calculating Derivatives
162
Vector Functions and Partial Separability
183
Notes and References
189
Properties of SR1 Updating
205
4
211
Notes and References
219
Algorithms for Partially Separable Functions
244
Nonlinear LeastSquares Problems
251
Notes and References
310
2
319
3
331
Notes and References
483
Algorithmic Framework
492
3
510
Sequential Quadratic Programming
528
9
558
A Background Material
576
A 1
582
References
609
222
620
Index 623
622
Notes and References
632
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