首页 | 本学科首页   官方微博 | 高级检索  
     


Sequential Quadratic Programming Methods for Large-Scale Problems
Authors:Walter Murray
Affiliation:(1) Systems Optimization Laboratory, Department of Operations Research, Stanford University, USA
Abstract:Sequential quadratic (SQP) programming methodsare the method of choice when solving small or medium-sized problems. Sincethey are complex methods they are difficult (but not impossible) to adapt tosolve large-scale problems. We start by discussing the difficulties that needto be addressed and then describe some general ideas that may be used toresolve these difficulties. A number of SQP codes have been written to solve specific applications and there is a general purposed SQP code called SNOPT,which is intended for general applications of a particular type. These aredescribed briefly together with the ideas on which they are based. Finally wediscuss new work on developing SQP methods using explicit second derivatives.
Keywords:nonlinearly constrained minimization  quadratic programming  large-scale optimization
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号