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Published in:
2005 | OriginalPaper | Chapter
Hierarchical Bayesian Optimization Algorithm
Author : Martin Pelikan
Published in: Hierarchical Bayesian Optimization Algorithm
Publisher: Springer Berlin Heidelberg
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The previous chapter has discussed how hierarchy can be used to reduce problem complexity in black-box optimization. Additionally, the chapter has identified the three important concepts that must be incorporated into black-box optimization methods based on selection and recombination to provide scalable solution for difficult hierarchical problems. Finally, the chapter proposed a number of artificial problems that can be used to test scalability of optimization methods that attempt to exploit hierarchy.