Greedy Decremental Quick Hypervolume Subset Selection Algorithms-Reference-Cited by-同舟云学术

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Greedy Decremental Quick Hypervolume Subset Selection Algorithms

Published:2022 Issue: Volume: Page:164-178
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Jaszkiewicz Andrzej^ORCID,Zielniewicz Piotr^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-14721-0_12

Reference38 articles.

1. Bader, J., Deb, K., Zitzler, E.: Faster hypervolume-based search using monte carlo sampling. In: Ehrgott, M., Naujoks, B., Stewart, T.J., Wallenius, J. (eds.) Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems, pp. 313–326. Springer, Berlin (2010). https://doi.org/10.1007/978-3-642-04045-0_27

2. Bader, J., Zitzler, E.: HypE: an algorithm for fast hypervolume-based many-objective optimization. Evol. Comput. 19(1), 45–76 (2011)

3. Basseur, M., Derbel, B., Goëffon, A., Liefooghe, A.: Experiments on greedy and local search heuristics for dimensional hypervolume subset selection. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2016, pp. 541–548. Association for Computing Machinery, New York (2016). https://doi.org/10.1145/2908812.2908949

4. Beume, N., Fonseca, C.M., Lopez-Ibanez, M., Paquete, L., Vahrenhold, J.: On the complexity of computing the hypervolume indicator. IEEE Trans. Evol. Comput. 13(5), 1075–1082 (2009)

5. Beume, N., Naujoks, B., Emmerich, M.: Sms-emoa: multiobjective selection based on dominated hypervolume. Euro. J. Operat. Res. 181, 1653–1669 (2007). https://doi.org/10.1016/j.ejor.2006.08.008

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On-line Quick Hypervolume Algorithm;Proceedings of the Companion Conference on Genetic and Evolutionary Computation;2023-07-15

2. Benchmarking large-scale subset selection in evolutionary multi-objective optimization;Information Sciences;2023-04

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