IMPROVED GENETIC ALGORITHM ON ATTRIBUTE REDUCTS BASED ON VARIABLE PRECISION ROUGH SET THEORY

The main objective of the paper is to introduce a new algorrithm of attribute reducts based on variable precision rough set theory. An improved genetic algorithm (GA) which adopts information entropy as it’s fitness function is introduced. The strategy of mixed crossover and two points mutation enlarges the search scope. The cross generation elicit selection and self-adapting strategy make the genetic algorithm converge to the overall optimal solution stably and quickly, which gives it an edge over the normal GA. The effectiveness and the advantage with respect to the norm GA are checked though an example.