基于遗传算法的模糊优化研究

Study on Fuzzy Optimization Based on Genetic Algorithm

针对约束条件、系数和优化变量均为模糊数形式的线性和非线性全模糊优化问题 ,利用模糊数积分排序方法 ,提出了基于遗传算法的模糊优化问题求解方法 ,在该方法中对优化变量采用模糊数编码(每个变量用三个实数编码 ,对应三角模糊数中的 a,b,c) ,最后通过全模糊线性和非线性优化算例 。

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.