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A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades - Part A.

, , , , , и . IEEE Trans. Evol. Comput., 25 (4): 609-629 (2021)

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Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation., , и . CoRR, (2020)A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades - Part A., , , , , и . IEEE Trans. Evol. Comput., 25 (4): 609-629 (2021)Automatic adaptation of hypermutation rates for multimodal optimisation., , и . FOGA, стр. 4:1-4:12. ACM, (2021)On inversely proportional hypermutations with mutation potential., , и . GECCO, стр. 215-223. ACM, (2019)Robust Optimization Over Time by Estimating Robustness of Promising Regions., , , , , и . IEEE Trans. Evol. Comput., 27 (3): 657-670 (2023)A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades - Part B., , , , , и . IEEE Trans. Evol. Comput., 25 (4): 630-650 (2021)Artificial immune systems for combinatorial optimisation: a theoretical investigation.. University of Sheffield, UK, (2020)British Library, EThOS.When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms., , и . Theor. Comput. Sci., (2020)Artificial immune systems can find arbitrarily good approximations for the NP-hard number partitioning problem., , и . Artif. Intell., (2019)Fast Immune System-Inspired Hypermutation Operators for Combinatorial Optimization., , и . IEEE Trans. Evol. Comput., 25 (5): 956-970 (2021)