Abstract
This paper proposes rough genetic algorithms based on the notion of rough values. A rough value is defined using an upper and a lower bound. Rough values can be used to effectively represent a range or set of values. A gene in a rough genetic algorithm can be represented using a rough value. The paper describes how this generalization facilitates development of new genetic operators and evaluation measures. The use of rough genetic algorithms is demonstrated using a simple document retrieval application.
Cite
CITATION STYLE
Lingras, P., & Davies, C. (1999). Rough genetic algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1711, pp. 38–46). Springer Verlag. https://doi.org/10.1007/978-3-540-48061-7_7
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