Applications of rough genetic algorithms

This paper describes rough genetic algorithms based on the notion of interv al values. A gene in a rough genetic algorithm can be represented using an interval. The paper explains how this generalization facilitates developmen t of new genetic operators and evaluation measures. Various operations of r ough genetic algorithms arc illustrated using a simple document retrieval e xample. An experiment involving classification of interval-valued traffic p atterns demonstrates the usefulness of rough genetic algorithms for real-wo rld applications. A discussion on further extensions of rough genetic algor ithms to rough sets is also included.