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Search Dynamics on Multimodal Multi-Objective Problems.

08:00 EDT 28th September 2018 | BioPortfolio

Summary of "Search Dynamics on Multimodal Multi-Objective Problems."

We continue recent work on the definition of multimodality in multi-objective optimization (MO) and the introduction of a test-bed for multimodal MO problems. This goes beyond well-known diversity maintenance approaches but instead focuses on the landscape topology induced by the objective functions. More general multimodal MO problems are considered by allowing ellipsoid contours for single-objective subproblems. An experimental analysis compares two MO algorithms, one that explicitly relies on hypervolume gradient approximation, and one that is based on local search, both on a selection of generated example problems. We do not focus on performance but on the interaction induced by the problems and algorithms, which can be described by means of specific characteristics explicitly designed for the multimodal MO setting. Furthermore, we widen the scope of our analysis by additionally applying visualization techniques in the decision space. This strengthens and extends the foundations for Exploratory Landscape Analysis (ELA) in MO.

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This article was published in the following journal.

Name: Evolutionary computation
ISSN: 1530-9304
Pages: 1-30

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