Improvement of Hybrid Intelligent Algorithm and Application in Fuzzy Programming

摘要

Fuzzy programming problem is solved by the hybrid intelligent algorithm at present, which can be computed effectively and used widespread. In the paper, fuzzy programming is presented briefly and the modeling principle of fuzzy programming is summarized. The limitation of genetic algorithm is analyzed, which exists in traditional hybrid intelligent algorithm. In order to increase the probability of escaping from the local optima, a new hybrid intelligent algorithm is proposed. The algorithm is combined with evolution strategies and simulated annealing which improves the precision. The evolution operator and selection operator are ameliorated by evolution strategies, while the mutation operator is ameliorated by simulated annealing. Then the algorithm steps are introduced and numerical results show that the new algorithm is superior to the traditional one on accuracy. Finally, the development prospect and direction of hybrid intelligent algorithm are proposed.