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PRECONDITIONED SPECTRAL PROJECTED GRADIENT METHOD ON CONVEX SETS
作者姓名:LenysBello  MarcosRaydan
作者单位:[1]Dpto.deMatemdtica,FacultaddeCiencias(FACYT),UniversidaddeCarabobo,Valencia,Venezuela [2]Dpto.deComputación,UniversidadCentraldeVenezuela,Ap.47002,Caracas1041-A,Venezuela
摘    要:The spectral gradient method has proved to be effective for solving large-scale unconstrained optimization problems. It has been recently extended and combined with the projected gradient method for solving optimization problems on convex sets. This combination includes the use of nonmonotone line search techniques to preserve the fast local convergence. In this work we further extend the spectral choice of steplength to accept preconditioned directions when a good preconditioner is available. We present an algorithmthat combines the spectral projected gradient method with preconditioning strategies toincrease the local speed of convergence while keeping the global properties. We discuss implementation details for solving large-scale problems.

关 键 词:光谱梯度法  目标梯度法  预处理  无约束最优化  非单调线性搜索
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