一种新的适应度函数，用于发现约束满足问题的大量可满足解

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) Pub Date : 2000-07-16 DOI:10.1109/CEC.2000.870783

H. Handa, O. Katai, T. Konishi, Mitsuru Baba

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引用次数: 2

摘要

本文讨论了遗传算法在一个约束满足问题实例中，在单次执行中可以找到多少个可满足解。因此，我们提出了一个新的适应度函数框架，它可以应用于传统的适应度函数。然而，所提出的适应度函数的机制非常简单，在各种一般约束满足问题的实例上的几个实验结果证明了所提出的适应度函数的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A new fitness function for discovering a lot of satisfiable solutions in constraint satisfaction problems

In this paper, we discuss how many satisfiable solutions a genetic algorithm can find in a problem instance of a constraint satisfaction problems in a single execution. Hence, we propose a framework for a new fitness function which can be applied to traditional fitness functions. However, the mechanism of the proposed fitness function is quite simple, and several experimental results on a variety of instances of general constraint satisfaction problems demonstrate the effectiveness of the proposed fitness function.

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Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)

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