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2015 | OriginalPaper | Buchkapitel

Geometric Differential Evolution in MOEA/D: A Preliminary Study

verfasst von : Saúl Zapotecas-Martínez, Bilel Derbel, Arnaud Liefooghe, Hernán E. Aguirre, Kiyoshi Tanaka

Erschienen in: Advances in Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is an aggregation-based algorithm which has became successful for solving multi-objective optimization problems (MOPs). So far, for the continuous domain, the most successful variants of MOEA/D are based on differential evolution (DE) operators. However, no investigations on the application of DE-like operators within MOEA/D exist in the context of combinatorial optimization. This is precisely the focus of the work reported in this paper. More particularly, we study the incorporation of geometric differential evolution (gDE), the discrete generalization of DE, into the MOEA/D framework. We conduct preliminary experiments in order to study the effectiveness of gDE when coupled with MOEA/D. Our results indicate that the proposed approach is able to outperform the standard version of MOEA/D, when solving a combinatorial optimization problem having between two and four objective functions.

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Vorheriges Kapitel Finding the Optimal Sample Based on Shannon’s Entropy and Genetic Algorithms

Nächstes Kapitel Energy Efficient Routing Based on NSGA-II for Context Parameters Aware Sensor Networks

Note, however, that in the minimization case \(d_1 = \frac{||(\varvec{F}(\varvec{x}) -\varvec{z}^{\star } )^\intercal \mathbf {\lambda }||}{||\mathbf {\lambda }||}\), \(d_2 = \left| \left| (\mathbf {F}(\mathbf {x}) - \right. \right. \) \(\left. \left. \mathbf {z}^{\star }) - d_1\frac{\mathbf {\lambda }}{||\mathbf {\lambda }||}\right| \right| \) and the reference point is such that \(\forall i\in \{1,\ldots ,M\},\forall \mathbf {x}\in X, z^\star <f_i(\mathbf {x})\).

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Titel: Geometric Differential Evolution in MOEA/D: A Preliminary Study
verfasst von: Saúl Zapotecas-Martínez
Bilel Derbel
Arnaud Liefooghe
Hernán E. Aguirre
Kiyoshi Tanaka
Verlag: Springer International Publishing
Buch: Advances in Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-27059-3

Electronic ISBN: 978-3-319-27060-9

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-27060-9_30

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