A NONMONOTONE LINE SEARCH FILTER METHOD WITH REDUCED HESSIAN UPDATING FOR NONLINEAR OPTIMIZATION 被引量：1

A NONMONOTONE LINE SEARCH FILTER METHOD WITH REDUCED HESSIAN UPDATING FOR NONLINEAR OPTIMIZATION

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摘要 This paper proposes a nonmonotone line search filter method with reduced Hessian updating for solving nonlinear equality constrained optimization.In order to deal with large scale problems,a reduced Hessian matrix is approximated by BFGS updates.The new method assures global convergence without using a merit function.By Lagrangian function in the filter and nonmonotone scheme,the authors prove that the method can overcome Maratos effect without using second order correction step so that the locally superlinear convergence is achieved.The primary numerical experiments are reported to show effectiveness of the proposed algorithm.

作者 GU Chao ZHU Detong

机构地区 School of Mathematics and Informatics Business College

出处《Journal of Systems Science & Complexity》 SCIE EI CSCD 2013年第4期534-555,共22页 系统科学与复杂性学报（英文版）

基金 supported by the National Science Foundation of China under Grant No.10871130 the Ph.D Foundation under Grant No.20093127110005 the Shanghai Leading Academic Discipline Project under Grant No.S30405 the Innovation Program of Shanghai Municipal Education Commission under Grant No.12YZ174

关键词 CONVERGENCE filter method lagrangian function line search maratos effect nomnono- tone. 非单调线搜索非线性优化黑森州过滤器 Hessian矩阵等式约束优化拉格朗日函数超线性收敛

分类号 O224 [理学—运筹学与控制论]

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