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On the Effect of Scalarising Norm Choice in a ParEGO implementation Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Toward Step-Size Adaptation in Evolutionary Multiobjective Optimization

Authors : Simon Wessing, Rosa Pink, Kai Brandenbusch, Günter Rudolph

Published in: Evolutionary Multi-Criterion Optimization

Publisher: Springer International Publishing

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Abstract

We give a definition for step size optimality in multiobjective optimization and visualize the optimal step sizes for a few two-dimensional example constellations. After that, we try to engineer a step size adaptation mechanism that also works in the real world. For this mechanism, we employ the self-adaptation of mutation strength, which is simple and well-known from single-objective optimization. The resulting approach obtains better results than simulated binary crossover and polynomial mutation on the bi-objective BBOB testbed.

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previous chapter Hypervolume Indicator Gradient Ascent Multi-objective Optimization
next chapter Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time
Footnotes
1
We are using step size and mutation strength synonymously in this work.
 
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Metadata
Title
Toward Step-Size Adaptation in Evolutionary Multiobjective Optimization
Authors
Simon Wessing
Rosa Pink
Kai Brandenbusch
Günter Rudolph
Copyright Year
2017
Book
Evolutionary Multi-Criterion Optimization

Print ISBN: 978-3-319-54156-3

Electronic ISBN: 978-3-319-54157-0

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-54157-0_45

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