PRECONDITIONED SPECTRAL PROJECTED GRADIENT METHOD ON CONVEX SETS

• 来源期刊: 计算数学（英文版）
• 关键词: Spectral gradient method Projected gradient method Preconditioning techniques Nonmonotone line search.
• 年，卷（期）: 2005,（3）
• 页码范围: 225-232
• 页数: 8页
• 语种: 英文

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 algorithm that combines the spectral projected gradient method with preconditioning strategies to increase the local speed of convergence while keeping the global properties. We discuss implementation details for solving large-scale problems.