文献类型：会议论文

英文题名：Dynamic filled algorithm for global optimization of nonlinear programming

作者：Ma, Wenwen[1]; Song, Jie[1]; Wang, Wei[1]

机构：[1] Department of Mathematics, East China University of Science and Technology, Shanghai, China

会议论文集：ICINA 2010 - 2010 International Conference on Information, Networking and Automation, Proceedings

语种：英文

外文关键词：Hopfield neural networks - Dynamical systems

摘要：Combined the advantage of Hopfield neural network and filled function method, a dynamic filled algorithm will be presented for constrainted global optimization of nonlinear programming. The algorithm contains two phases. The dynamic minimizing phase in which the dynamic minimizing system is used to find the local minimizer of the global optimization. And in the dynamic filled phase, a new initial condition in a lower basin can be determined by the dynamic filled system. By repeating two dynamic systems of the algorithm, a global minimal point can be obtained at last. The algorithm not only makes the computation simple, rapid, and criterion, but also prevents the Hopfield neural network from getting trapped in the local minima. ? 2010 IEEE.