Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/83700| Author(s): | R. M. A. Silva M. G. C. Resende P. M. Pardalos J. F. Gonçalves |
| Title: | Biased random-key genetic algorithm for bound-constrained global optimization |
| Issue Date: | 2012 |
| Abstract: | Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a biased random-key genetic algorithm for finding approximate solutions for continuous global optimization problems subject to box constraints. Experimental results illustrate its effectiveness on the robot kinematics problem, a challenging problem according to [7]. |
| Subject: | Estudos de gestão, Economia e gestão Management studies, Economics and Business |
| Scientific areas: | Ciências sociais::Economia e gestão Social sciences::Economics and Business |
| URI: | https://hdl.handle.net/10216/83700 |
| Source: | GOW 2012: Proceedings of Global Optimization Workshop |
| Document Type: | Artigo em Livro de Atas de Conferência Internacional |
| Rights: | openAccess |
| License: | https://creativecommons.org/licenses/by-nc/4.0/ |
| Appears in Collections: | FEP - Artigo em Livro de Atas de Conferência Internacional |
This item is licensed under a Creative Commons License
