nk模型中的遗传熵算法

Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI:10.1109/ICEC.1997.592263

Chang-Yong Lee, S. Han

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引用次数: 1

摘要

提出了一种新的组合优化算法——遗传熵算法。为了验证该算法，我们采用NK模型，并将遗传熵算法与传统遗传算法的性能进行了比较。K值越高，该算法的性能越好。讨论了该算法的特点以及两种算法的区别。

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Genetic-entropic algorithm in NK-model

A new combinatorial optimization algorithm, genetic entropic algorithm, is proposed. To test the algorithm, we adopt the NK model and compare the performances of the genetic entropic algorithm with those of the conventional genetic algorithm. The higher the K value, the better this algorithm performs. The characteristics of this algorithm together with the difference between two algorithms are discussed.

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Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)

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