Local convergence of predictor-corrector infeasible-interior-point algorithms for SDPs and SDLCPs

作     者：Kojima, M Shida, M Shindoh, S 

作者机构：Tokyo Inst Technol Dept Math & Comp Sci Meguro Ku Tokyo 152 Japan Kanagawa Univ Dept Math Kanagawa Ku Yokohama Kanagawa 221 Japan Natl Def Acad Dept Math & Phys Yokosuka Kanagawa 239 Japan 

出 版 物：《MATHEMATICAL PROGRAMMING》 (数学规划)

年 卷 期：1998年第80卷第2期

页      面：129-160页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0835[工学-软件工程] 0701[理学-数学] 

主　　题：semidefinite programming infeasible-interior-point method predictor-corrector-method superlinear convergence primal-dual nondegeneracy 

摘      要：An example of an SDP (semidefinite program) exhibits a substantial difficulty in proving the superlinear convergence of a direct extension of the Mizuno-Todd-Ye type predictor-corrector primal-dual interior-point method for LPs (linear programs) to SDPs, and suggests that we need to force the generated sequence to converge to a solution tangentially to the central path (or trajectory). A Mizuno-Todd-Ye type predictor-corrector infeasible-interior-point algorithm incorporating this additional restriction for monotone SDLCPs (semidefinite linear complementarity problems) enjoys superlinear convergence under strict complementarity and nondegeneracy conditions. (C) 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.