带有线搜索的非单调自适应新锥模型信赖域算法

Abstract

Abstract:

A trust region algorithm based on new conic model is presented for unconstrained optimization by combining the nonmonotonic wolfe line search and quasi-newton technique.A new trust region subproblem is constructed,in which the trust region radius uses the information of g_kand B_k.The subproblem is solved by using c^p||B^-1_k+1|| ||g_k+1||],c∈(0,1),p is a nonnegative integer.Therefore,instead of adjusting Δ_k,one adjusts p for each iteration.Under proper assumptions,the global convergence of the method is proved.

Key words: unconstrained optimization;nonmonotonic line search;quasi-newton;new conic model;trust region method;global convergence

CLC Number:

O221

LI Xiaowei,QIAN Huimin. A Quasi-Newton Nonmonotone Trust Region Method of New Conic Model[J]., 2013, 26(11): 4-.

References

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A Quasi-Newton Nonmonotone Trust Region Method of New Conic Model

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