Study on Fuzzy Optimization Based on Genetic Algorithm
基于遗传算法的模糊优化研究

Using fuzzy numbers ranking this paper presents a method based on genetic algorithm to solving fully fuzzy linear and nonlinear optimization problems that the constrain conditions, coefficients and optimum variables are fuzzy numbers. In the method the variables are encoded as triangular fuzzy numbers, i.e., a variable is represented by three real numbers which are a,b and c of a triangular fuzzy number respectively. It can be concluded that the method is efficient and practicable by means of fully fuzzy linear and nonlinear optimization examples.