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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Yevseyeva, I., Vitor Basto-Fernandes & Grácio, José (2012). Review on multiobjective evolutionary algorithms and application in metal matrix composites. International Review of Mechanical Engineering. 6 (3), 507-519
Exportar Referência (IEEE) 
I. Yevseyeva et al.,  "Review on multiobjective evolutionary algorithms and application in metal matrix composites", in Int. Review of Mechanical Engineering, vol. 6, no. 3, pp. 507-519, 2012
Exportar BibTeX 
@article{yevseyeva2012_1715025396500,
	author = "Yevseyeva, I. and Vitor Basto-Fernandes and Grácio, José",
	title = "Review on multiobjective evolutionary algorithms and application in metal matrix composites",
	journal = "International Review of Mechanical Engineering",
	year = "2012",
	volume = "6",
	number = "3",
	pages = "507-519",
	url = "http://connection.ebscohost.com/c/articles/82565319/review-multiobjective-evolutionary-algorithms-application-metal-matrix-composites"
}
Exportar RIS 
TY  - JOUR
TI  - Review on multiobjective evolutionary algorithms and application in metal matrix composites
T2  - International Review of Mechanical Engineering
VL  - 6
IS  - 3
AU  - Yevseyeva, I.
AU  - Vitor Basto-Fernandes
AU  - Grácio, José
PY  - 2012
SP  - 507-519
SN  - 1970-8734
UR  - http://connection.ebscohost.com/c/articles/82565319/review-multiobjective-evolutionary-algorithms-application-metal-matrix-composites
AB  - This work presents a review on evolutionary algorithms when applied to problems with multiple objectives to be optimized simultaneously. Evolutionary algorithms are well-known optimization techniques utilized in situations where exact methods fail, in particular, in case of optimization of complex, non-convex, non-differentiable, non-smooth and/or discontinuous functions that are common to the real engineering applications, or used for solving combinatorial NP-hard problems, for instance encountered in the search of optimal combination of several parameters. These techniques are shown to be efficient in finding at least sub-optimal solution(s) when solving problems of mentioned complexity. In this work, the recent multiobjective evolutionary algorithms are presented and the potential application of multiobjective evolutionary algorithms in product development is illustrated.
ER  -