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On filter-successive linearization methods for nonlinear semidefinite programming 被引量:18

On filter-successive linearization methods for nonlinear semidefinite programming
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摘要 In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially efficient. In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially effcient.
出处 《Science China Mathematics》 SCIE 2009年第11期2341-2361,共21页 中国科学:数学(英文版)
基金 supported by National Natural Science Foundation of China (Grant No. 10871098) Science Foundation of Jiangsu Province (Grant No. BK2006214)
关键词 semidefinite programming nonlinear optimization successive linearization method filter method global convergence 65K05 90C30 semidefinite programming nonlinear optimization successive linearization method filter method global convergence
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