The research and application on improved intelligence optimization algorithm based on knowledge base
The current intelligence optimization algorithm has the limitation of slow search, stagnation and easy falling into local optimum. So the algorithm characteristic was researched, and the improved intelligence optimization algorithm based on knowledge base was proposed. The cases, experiences and rules facing different kinds of model were stored in the knowledge base, which guided intelligence optimization algorithm to generate initial state and improve search strategy. The evaluation indexes of intelligence optimization algorithm were proposed, including optimization performance, time performance and robustness performance. The Chinese Traveling Salesman Problem (CTSP) was solved by improved ant colony algorithm based on knowledge base, the result shows that the improved algorithm could get better performances. The improved algorithm could solve the problem of design, decision and scheduling more effectively.
Knowledge base intelligence optimization algorithm ant colony algorithm CTSP
Sun Yong Li Zenglu Li Wenwei Yi Zhongkai Li Guangyun Xue Jirong
Science Research Institute of China North Industries Group Corporation Beijing 100089 China
国际会议
杭州
英文
661-665
2012-03-23（万方平台首次上网日期，不代表论文的发表时间）