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Titlebook: Evolutionary Computing; AISB Workshop, Leeds Terence C. Fogarty Conference proceedings 1994 Springer-Verlag Berlin Heidelberg 1994 algorith

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樓主: exterminate
61#
發(fā)表于 2025-4-1 02:16:03 | 只看該作者
Exploiting mate choice in evolutionary computation: Sexual selection as a process of search, optimiwering plants. Over the short term, mate preferences evolve because they improve the outcome of sexual recombination. Over the long term, assortative mate preferences can help maintain genetic diversity, promote speciation, and facilitate evolutionary search through optimal outbreeding; selective ma
62#
發(fā)表于 2025-4-1 09:14:27 | 只看該作者
An empirical comparison of selection methods in evolutionary algorithms,by observing the rate of convergence on three idealised problems. The first considers selection only, the second introduces mutation as a source of variation, the third also adds in evaluation noise. Fitness proportionate selection suffers from scaling problems: a number of techniques to reduce thes
63#
發(fā)表于 2025-4-1 14:01:06 | 只看該作者
64#
發(fā)表于 2025-4-1 18:12:30 | 只看該作者
65#
發(fā)表于 2025-4-1 18:28:44 | 只看該作者
Genetic algorithms and neighbourhood search, many situations in which the simple GA does not perform particularly well, and various methods of . have been proposed. These often involve incorporating other methods such as . or . as an ‘a(chǎn)dd-on’ extra to the basic GA strategy of selection and reproduction..Here, we explore an alternative perspec
66#
發(fā)表于 2025-4-1 23:49:02 | 只看該作者
A unified paradigm for parallel Genetic Algorithms,al components of a standard, sequential GA. The only difference with the sequential GA is in the computation speed. The second approach more closely resembles the real life simultaneous evolution of species, which is the central theme in GAs. Algorithms following this approach are still referred to
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