Improved Intuitionistic Fuzzy Programming Based on Differential Evolution Algorithm

For Plamen¿s intuitionistic fuzzy programming model needs to consider the degrees of rejection of objective and of constraints together with the degrees of satisfaction, its arithmetic complexity is twice as fuzzy programming. An improved intuitionistic fuzzy programming model is proposed. At the first stage, only the rejection degrees of objective and constraints are considered, which make minimums concentrate around the global minimum. At the second stage, only the satisfaction degrees of objective and constraints are considered, which make minimums move towards global minimum. So its arithmetic complexity is only half of Plamen¿s intuitionistic fuzzy programming model. Then, improved intuitionistic fuzzy nonlinear programming is resolved by differential evolution algorithm, DE/rand/1 and DE/best/1 mutation operators are used in two stages separately. At last, Benchmarks testing functions validate stability and validity of the model.