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Titlebook: Genetic Programming; 9th European Confere Pierre Collet,Marco Tomassini,Anikó Ekárt Conference proceedings 2006 Springer-Verlag Berlin Heid

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11#
發(fā)表于 2025-3-23 10:51:37 | 只看該作者
12#
發(fā)表于 2025-3-23 16:23:50 | 只看該作者
https://doi.org/10.1007/978-3-642-71980-6presentation, efficient GP operators are introduced that allow efficient and fast evolution, as witnessed by the results on two construction problems that demonstrate that the proposed approach is able to achieve both compactness and reusability of evolved components.
13#
發(fā)表于 2025-3-23 19:15:45 | 只看該作者
https://doi.org/10.1007/978-3-663-14655-1parison between crossover and mutation variation operators, and also undirected random search. We found that the evolutionary algorithms performed much better than undirected random search, and thats mutation outperformed crossover on most problems.
14#
發(fā)表于 2025-3-24 01:58:44 | 只看該作者
15#
發(fā)表于 2025-3-24 05:29:24 | 只看該作者
Zwei postkommunistische Parteien und Europagorithm incorporated by Incentive method. Experimental results are compared with results from a penalty method and from a non-constraint setting. Statistic analysis suggests that Incentive Method is more effective than the other two techniques for this specific problem.
16#
發(fā)表于 2025-3-24 08:45:49 | 只看該作者
Die Wissenschaften der Lebensverl?ngerungg salesman problem. Results show that the concept can be used to solve hard problems of big size reliably achieving comparably good or better results than classical evolutionary algorithms and other selected methods.
17#
發(fā)表于 2025-3-24 14:04:22 | 只看該作者
Incentive Method to Handle Constraints in Evolutionary Algorithms with a Case Studygorithm incorporated by Incentive method. Experimental results are compared with results from a penalty method and from a non-constraint setting. Statistic analysis suggests that Incentive Method is more effective than the other two techniques for this specific problem.
18#
發(fā)表于 2025-3-24 18:32:35 | 只看該作者
Iterative Prototype Optimisation with Evolved Improvement Stepsg salesman problem. Results show that the concept can be used to solve hard problems of big size reliably achieving comparably good or better results than classical evolutionary algorithms and other selected methods.
19#
發(fā)表于 2025-3-24 22:37:58 | 只看該作者
20#
發(fā)表于 2025-3-25 01:00:56 | 只看該作者
https://doi.org/10.1007/978-3-8349-3530-4series and on the Arosa Ozone time series. The results show that the method is effective in obtaining the analytical expression of the first two problems, and in achieving a very good approximation and forecasting of the third.
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