Applications of Rough Genetic Algorithms
Pawan J. Lingras, Cedric Davies · Computational Intelligence · 2001
This paper describes rough genetic algorithms based on the notion of interval values. A gene in a rough genetic algorithm can be represented using an interval. The paper explains how this generalization facilitates development of new genetic operators and evaluation measures. Various operations of rough genetic algorithms are illustrated using a simple document retrieval example. An experiment involving classification of interval‐valued traffic patterns demonstrates the usefulness of rough genetic algorithms for real‐world applications. A discussion on further extensions of rough genetic algorithms to rough sets is also included.