An Expedition to Multimodal Multi-objective Optimization Landscapes

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Contributors

Abstract

The research in evolutionary multi-objective optimization is largely missing a notion of functional landscapes, which could enable a visual understanding of multimodal multi-objective landscapes and their characteristics by connecting decision and objective space. This consequently leads to the negligence of decision space in most algorithmic approaches and an almost complete lack of Exploratory Landscape Analysis (ELA) tools. This paper dares a first step into this unexplored field based on gradient properties of the multi-objective landscape. For a first time, basins of attraction and superpositions of local optima are visualized and thereby made intuitively accessible. With this work, we hope to highlight the importance of detailed decision space analysis in multi-objective optimization and to stimulate further research in that direction.

Details

Original languageEnglish
Title of host publication9th International Conference on Evolutionary Multi-Criterion Optimization
Publication statusPublished - 19 Feb 2017
Peer-reviewedYes

External IDs

Scopus 85014290028