求解非线性规划问题的改进直觉模糊遗传算法

提出一种改进的直觉模糊遗传算法用于求解带有多维约束的非线性规划问题。以遗传算法在迭代寻优中的个体适应度大小构造相应可行解的隶属度和非隶属度函数,将非线性规划问题直觉模糊化转化为直觉模糊非线性规划问题,通过建立直觉模糊推理系统,自适应地调节遗传算法的交叉率和变异率；并采用一种改进的选择策略,将个体按适应度值大小排序、等量分组,对适应度低的个体组随机选择复制,保留不可行解中可能隐含的有利寻优信息,增强种群个体的多样性和竞争性。仿真实验结果表明,该算法求解非线性规划问题时是可行和有效的。

Improved Intuitionistic Fuzzy Genetic Algorithm for Nonlinear Programming Problems

To solve the multidimensional nonlinear programming problem,an improved intuitionistic fuzzy genetic algorithm(IFGA) was proposed.The membership and nonmembership degrees of individuals are defined by the individual fitness of the genetic algorithm in each iteratine optimization,and the problem is transformed to the intuitionistic fuzzy nonlinear programming problem to adjust crossover and mutation rates.And the paper proposed an improved selection operator.The individuals are divided into four same size groups,and the group with poor fitness is selected and copied randomly to increase the diversity and competitiveness,because the implicit optimization information of non-feasible solution is reserved.The simulation results indicate the IFGA is feasible and effective.