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| Preface | ||
| 1 | Congested O-D Trip Demand Adjustment Problem: Bilevel Programming Formulation and Optimality Conditions | 1 |
| 2 | Determining Tax Credits for Converting Nonfood Crops to Biofuels: An Application of Bilevel Programming | 23 |
| 3 | Multilevel Optimization Methods in Mechanics | 51 |
| 4 | Optimal Structural Design in Nonsmooth Mechanics | 91 |
| 5 | Optimizing the Operations of an Aluminium Smelter Using Non-Linear Bi-Level Programming | 117 |
| 6 | Complexity Issues in Bilevel Linear Programming | 149 |
| 7 | The Computational Complexity of Multi-Level Bottleneck Programming Problems | 165 |
| 8 | On the Linear Maxmin and Related Programming Problems | 181 |
| 9 | Piecewise Sequential Quadratic Programming for Mathematical Programs with Nonlinear Complementarity Constraints | 209 |
| 10 | A New Branch and Bound Method for Bilevel Linear Programs | 231 |
| 11 | A Penalty Method for Linear Bilevel Programming Problems | 251 |
| 12 | An Implicit Function Approach to Bilevel Programming Problems | 273 |
| 13 | Bilevel Linear Programming, Multiobjective Programming, and Monotonic Reverse Convex Programming | 295 |
| 14 | Existence of Solutions to Generalized Bilevel Programming Problem | 315 |
| 15 | Application of Topological Degree Theory to Complementarity Problems | 333 |
| 16 | Optimality and Duality in Parametric Convex Lexicographic Programming | 359 |
| Index | 381 |
| Price | Condition | Delivery | Seller | Action |
| $270.00 | Digital |
| WonderClub |
Charles Casey
reviewed Multilevel Optimization: Algorithms and Applications on December 31, 2012
Multilevel Optimization
I normally don't do this, but I'm going to copy/paste this review across three separate books: Chaitin's "The Unknowable", "The Limits of Mathematics", and "Exploring Randomness".
All three are all thin, overpriced, but very approachable books on Algorithmic Information Theory. Themes include:
- Undecidability, as the basis of formulating a new kind of randomness measure for numbers that have already been generated (not just restricting randomness measures to the processes that generate numbers).
- Chaitin's Omega constant, which is the probability that universal Turning machine will halt on random input. This constant is "maximally unknowable", but that doesn't stop one from performing math with it.
- Philosophy surrounding these topics.
One might underestimate Kolmogorov's contributions, given how ridiculously self-promoting Chaitin has been with this AIT. However, the topics are interesting enough that he's easy to forgive. And he uses many code demonstrations (LISP) to make concrete examples out of the math.
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