Neural network approach for semivectorial bilevel programming problem

摘要：

A novel neural network approach is proposed for solving semivectorial bilevel programming problem, where the upper level is a scalar-valued optimization problem and the lower level is the linear multiobjective programming. The proposed neural network is proved to be Lyapunov stable and capable of generating optimal solution to the semivectorial BP problem. The numerical result shows that the neural network approach is feasible and efficient.

关键词： semivectorial bilevel programming problem neural network asymptotic stability optimal solution

作者: Yibing Lv

作者单位: School of Information and Mathematics Yangtze University Jingzhou China

会议类型: 国际会议

会议名称: 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics 第4届智能人机系统与控制论国际会议 IHMSC 2012

会议地点: 南昌

会议语种:英文

页码: 390-393

在线出版日期: 2012-08-26（万方平台首次上网日期，不代表论文的发表时间）