Application research of fuzzy optimization based on genetic algorithm

Fuzzy optimization is commonly faced in productive practice and economic systems, while 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. Propose a kind of fuzzy genetic algorithm based on the level characteristics and point out how to implement it as well. Theoretical analyses and simulation test show that this kind of algorithm is of feasibility, operability and could be widely used in many problems.