Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion
US7739206B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 16, 2007 |
| Grant date | Jun 15, 2010 |
| Priority date | — |
| Expiry date | Apr 16, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2111/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for combining the model-based and genetics-based methods are combined according to a convergence criterion. When the population is not converged, the genetics-based approach is used, and when the population is converged, the model-based method is used to generate offspring. The algorithm benefits from using a model-based offspring generation only when the population shows a certain degree of regularity, i.e., converged in a stochastic sense. In addition, a more sophisticated method to construct the stochastic part of the model can be used. Also a biased Gaussian noise (the mean of the noise is not zero), as well as a white Gaussian noise (the mean of the noise is zero) can be preferably used for the stochastic part of the model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.