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 multimodal MO setting. By this means the foundation for Exploratory Landscape Analysis in MO is provided.
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Notes
- 1.
The HIGA-MO source code is available on moda.liacs.nl/index.php?page=code.
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Acknowledgments
Heike Trautmann, Pascal Kerschke, Mike Preuss and Christian Grimme acknowledge support by the European Research Center for Information Systems (ERCIS).
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Kerschke, P. et al. (2016). Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_90
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DOI: https://doi.org/10.1007/978-3-319-45823-6_90
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