Research on the Fuzzy Genetic Algorithm Based on Level Characteristics

Fuzzy optimization is common problem faced in productive practice and economic systems, so dealing with the uncertain information involved in it becomes the key point. Based on the level characteristic function, which describes the confidence degree of information with different levels, suggest a set of metric system for describing uncertain information. We propose a kind of fuzzy genetic algorithm based on the level characteristics and point out the implementation steps as well. Theoretical analysis and simulation tests show that this algorithm is of feasibility, operability and could be widely used in many problems.