Abstract
This paper formally defines multimodality in multiobjective optimization (MO). We introduce a test-bed in which multimodal MO problems with known properties can be constructed as well as numerical characteristics of the resulting landscape. Gradient- and local search based strategies are compared on exemplary problems together with specific performance indicators in the multimodalMO setting. By this means the foundation for Exploratory Landscape Analysis in MO is provided.
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CITATION STYLE
Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2016). Towards analyzing multimodality of continuous multiobjective landscapes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9921 LNCS, pp. 962–972). Springer Verlag. https://doi.org/10.1007/978-3-319-45823-6_90
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