Improvement of Hybrid Intelligent Algorithm and Application in Fuzzy Programming
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.
Zhenkui Pei Xia Hua Jian Liu
Department of Computational Intelligence and Machine Learning, College of Computer and Communication Department of Computational Intelligence and Application.College of Computer and Communication Engin Department of Computational Intelligence and Application, College of Computer and Communication Engi
国际会议
武汉
英文
298-301
2008-12-19（万方平台首次上网日期，不代表论文的发表时间）