Heuristic genetic algorithm for minimal reduction decision system based on rough set theory

Knowledge reduction is an important issue when dealing with huge amounts of data. And it has been proved that computing the minimal reduction of decision system is NP-complete. By introducing heuristic strategy, a heuristic genetic algorithm is proposed. A new operator implement is added to heuristic information, and can maintain the ability of classification. The operator is the embodiment of one local research method using heuristic information. So the algorithm can converge quickly and has the ability of optimizing globally. The correctness and effectiveness are shown in the experiments.