Constrained Dogleg methods for nonlinear systems with simple bounds

被引:24
作者
Bellavia, Stefania [1 ]
Macconi, Maria [1 ]
Pieraccini, Sandra [2 ]
机构
[1] Univ Florence, Dipartimento Energet S Stecco, I-50134 Florence, Italy
[2] Politecn Torino, Dipartimento Sci Matemat, I-10129 Turin, Italy
关键词
Bound-constrained equations; Diagonal scalings; Trust region methods; Dogleg methods; Newton methods; Global convergence; TRUST-REGION APPROACH; POINT NEWTON METHODS; OPTIMIZATION SOFTWARE; ALGORITHM; EQUATIONS; MINIMIZATION; CONVERGENCE;
D O I
10.1007/s10589-012-9469-8
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We focus on the numerical solution of medium scale bound-constrained systems of nonlinear equations. In this context, we consider an affine-scaling trust region approach that allows a great flexibility in choosing the scaling matrix used to handle the bounds. The method is based on a dogleg procedure tailored for constrained problems and so, it is named Constrained Dogleg method. It generates only strictly feasible iterates. Global and locally fast convergence is ensured under standard assumptions. The method has been implemented in the Matlab solver CoDoSol that supports several diagonal scalings in both spherical and elliptical trust region frameworks. We give a brief account of CoDoSol and report on the computational experience performed on a number of representative test problems.
引用
收藏
页码:771 / 794
页数:24
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