Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/83700Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | R. M. A. Silva | |
| dc.creator | M. G. C. Resende | |
| dc.creator | P. M. Pardalos | |
| dc.creator | J. F. Gonçalves | |
| dc.date.accessioned | 2022-09-12T02:45:17Z | - |
| dc.date.available | 2022-09-12T02:45:17Z | - |
| dc.date.issued | 2012 | |
| dc.identifier.other | sigarra:51592 | |
| dc.identifier.uri | https://hdl.handle.net/10216/83700 | - |
| dc.description.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]. | |
| dc.language.iso | eng | |
| dc.relation.ispartof | GOW 2012: Proceedings of Global Optimization Workshop | |
| dc.rights | openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Estudos de gestão, Economia e gestão | |
| dc.subject | Management studies, Economics and Business | |
| dc.title | Biased random-key genetic algorithm for bound-constrained global optimization | |
| dc.type | Artigo em Livro de Atas de Conferência Internacional | |
| dc.contributor.uporto | Faculdade de Economia | |
| dc.subject.fos | Ciências sociais::Economia e gestão | |
| dc.subject.fos | Social sciences::Economics and Business | |
| Appears in Collections: | FEP - Artigo em Livro de Atas de Conferência Internacional | |
This item is licensed under a Creative Commons License
