%0 Journal Article
%T A Modified SQP Parallel Variable Distribution Algorithm<br>修正的SQP型并行变量分配算法
%A FENG Ting-Ting
%A HAN Cong-Ying
%A HE Guo-Ping
%A <br>冯婷婷
%A 韩丛英
%A 贺国平
%J 数学物理学报(A辑)
%D 2012
%I 
%X Ferris and Mangasarian proposed a PVD(parallel variable distribution) algorithm for solving optimization problems, which divides variables into primary and secondary variables groups. According to the algorithm, the variables are distributed among p parallel processors with each processor having the responsibility for updating its primary variables while allowing the remaining "secondary" variables to change in a restricted fashion along some easily computable directions, which enhances robustness and flexibility of the algorithm. In this paper, we present a modified SQP type PVD algorithm based on 6], whose search direction is a suitable combination of a descent direction and a feasible direction, and give a second-order revised for such a  direction. This new algorithm is very effective in preventing Maratos effect from happening, and avoid constraints in subproblem are inconsistent. We show the global convergence under some suitable conditions.
%K Nonlinear programmingzz
%K Sequential quadratic programmingzz
%K PVD algorithmzz<br>非线性规划
%K 序列二次规划
%K PVD算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=37F46C35E03B4B86&jid=4DB553CDB5F521D8C921082E5C95EC80&aid=46DBF3E8FC2736F0D2316A32E2740C09&yid=99E9153A83D4CB11&vid=9971A5E270697F23&iid=0B39A22176CE99FB&sid=50EA2A80A7D254EF&eid=5957D6E0A50D26B5&journal_id=1003-3998&journal_name=数学物理学报(A辑)&referenced_num=0&reference_num=0