Benchmarking of Continuous Black Box Optimization Algorithms
Author:
Affiliation:
1. INRIA, France
Publisher
MIT Press - Journals
Subject
Computational Mathematics
Link
https://www.mitpressjournals.org/doi/pdf/10.1162/EVCO_e_00091
Cited by 8 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. DE/current−to−better/1: A new mutation operator to keep population diversity;Intelligent Systems with Applications;2022-05
2. Benchmarking large-scale continuous optimizers: The bbob-largescale testbed, a COCO software guide and beyond;Applied Soft Computing;2020-12
3. Selecting a diverse set of benchmark instances from a tunable model problem for black-box discrete optimization algorithms;Applied Soft Computing;2020-07
4. A new mutation operator with the ability to adjust exploration and exploitation for DE algorithm;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2019-07-13
5. Benchmarking the region learning-based JADE on noiseless functions;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2019-07-13
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