Hybrid algorithm based on cultural algorithm and modified differential evolution algorithm
基于文化算法和改进差分进化算法的混合算法

Modified differential evolution algorithm can not make effective use of knowledge about evolutionary information, and traditional cultural algorithm converge slowly because only mutation operation is adopted in population space. To solve these problems, a new hybrid optimization algorithm was proposed based on cultural algorithm and modified differential evolution algorithm. It was applied to constraint solving. Simulation tests were performed based on benchmark functions and the production scheduling problem of butene alkylation. The results indicate that the proposed algorithm is practicable and effective. Compared with other algorithms, it is superior in optimizing efficiency and results, and reduces the computational cost.