Non-convex multiobjective optimization under uncertainty: a descent algorithm. Application to sandwich plate design and reliability

In this paper a novel algorithm for solving multiobjective design optimization problems with non-smooth objective functions and uncertain parameters is presented. The algorithm is based on the existence of a common descent vector for each sample of the random objective functions and on an extension...

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Bibliographic Details
Published in:	Engineering optimization Vol. 51; no. 5; pp. 733 - 752
Main Authors:	Mercier, Q., Poirion, F., Désidéri, J. A.
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 04.05.2019 Taylor & Francis Ltd
Subjects:	Algorithms Computer Science Data Structures and Algorithms Descent Design optimization Engineering Sciences Genetic algorithms Materials Multiobjective optimization Multiple objective analysis Parallel processing Parameter uncertainty Reliability stochastic algorithm uncertainty INCERTITUDE ALGORITHME STOCHASTIQUE FIABILITE OPTIMISATION MULTIDISCIPLINAIRE
ISSN:	0305-215X, 1029-0273
Online Access:	Get full text
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