On efficient black box optimization of systems defined by 100 or more parameters - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2010

On efficient black box optimization of systems defined by 100 or more parameters

Résumé

In product development, the optimization of hectovariate systems (that is, depending on more than a hundred variables) is hard to handle with usual black box methods, since they require a huge number of experiments. That is an issue since each experiment can be both expensive and time-consuming. Furthermore, these methods can't even handle such big problems within a reasonable period of time. The Lean optimization algorithm [1] was one approach to overcome these difficulties. In this paper, we will come up with a new lean algorithm, inspired from [1] and developing new ideas. It will then be tested on some classical mathematical problems of various sizes and a practical example of combustion simulation engine issued from Volvo Technology. We will see that this new algorithm has a faster and more robust convergence, and is able to significantly improve most systems within a number of experiments less than the number of variables.
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Dates et versions

hal-01598044 , version 1 (29-09-2017)

Identifiants

  • HAL Id : hal-01598044 , version 1

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Olivier Goury, Sven Ahlinder. On efficient black box optimization of systems defined by 100 or more parameters. 2010. ⟨hal-01598044⟩
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