Abstract
We propose a new approach for multiobjective shape optimization based on the estimation of probability distributions. The algorithm improves search space exploration by capturing landscape information into the probability distribution of the population. Correlation among design variables is also used for the computation of probability distributions. The algorithm uses finite element method to evaluate objective functions and constraints. We provide several design problems and we show Pareto front examples. The design goals are: minimum weight and minimum nodal displacement, without holes or unconnected elements in the structure.
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© 2005 Springer-Verlag Berlin Heidelberg
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Peña, S.I.V., Rionda, S.B., Aguirre, A.H. (2005). Multiobjective Shape Optimization Using Estimation Distribution Algorithms and Correlated Information. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_46
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DOI: https://doi.org/10.1007/978-3-540-31880-4_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24983-2
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