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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
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
@article{yevseyeva2012_1734973299126, 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" }
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 -