Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization
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Abstract (arXiv)
This report presents benchmarking results of the Hill-Valley Evolutionary Algorithm version 2019 (HillVallEA19) on the CEC2013 niching benchmark suite under the restrictions of the GECCO 2019 niching competition on multimodal optimization. Performance is compared to algorithms that participated in previous editions of the niching competition.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Jul 2019.
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Citing papers per year: 2023: 1; 2024: 2.
3 papers.
- 2023Multimodal Optimization with k-Cluster Big Bang-Big Crunch Algorithm and Postprocessing Methods for Identification and Quantification of Optimacited by 1
- 2024Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimizationcited by 0
- 2024Multiple Global Peaks Big Bang-Big Crunch Algorithm for Multimodal Optimizationcited by 0
- 2024Multiple Global Peaks Big Bang-Big Crunch Algorithm for Multimodal Optimization8 Oct 2024
- 2024Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization29 Aug 2024
- 2023Multimodal Optimization with k-Cluster Big Bang-Big Crunch Algorithm and Postprocessing Methods for Identification and Quantification of Optima21 Dec 2023