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Black Box Optimization with Exact Subsolvers : a Radial Basis Function Algorithm for Problems with Convex Constraints.
| Call Number: | Libro Electrónico |
|---|---|
| Main Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Berlin :
Logos Verlag Berlin,
2016.
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| Subjects: | |
| Online Access: | Texto completo |
Table of Contents:
- Intro; 1 Introduction; 1.1 Expensive optimization problems; 1.2 Global optimization methods; 2 Optimization methods for expensive problems; 2.1 Surface methods; 2.2 Surface methods with radial basis functions; 2.3 Gutmann's RBF method; 3 An optimized choice of points to be evaluated; 3.1 The subproblems: Cheap global optimization problems; 3.2 Distances, properties of phi(r) and lower bounds for sn(x); 3.3 Useful properties of the matrix Phi and the (inverse of the) matrix A; 3.4 Computation of lower bounds for the auxiliary problem and the weighted auxiliary problem
- 3.5 The Branch and Bound algorithm4 Box partitioning; 4.1 The problem; 4.2 General bisection of d-dimensional rectangles; 5 General convex constraints; 5.1 Scaling down rectangles; 5.2 The modified Branch and Bound algorithm; 6 Numerical tests; 6.1 The implementation; 6.2 How to use the code; 6.3 Test instances and runtime; 7 Conclusions; A Testproblems; Bibliography