Modified subspace limited memory BFGS algorithm for large-scale bound constrained optimization

Authors:
Yunhai Xiao;Hongchuan Zhang
Affiliations:
Institute of Applied Mathematics, School of Mathematics and Information Science, Henan University, Kaifeng, Henan, 475004, PR China;College of Electric and Information Engineering, Hunan University, Changsha, 410082, PR China
Venue:
Journal of Computational and Applied Mathematics
Year:
2008

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Abstract

In this paper, a subspace limited memory BFGS algorithm for solving large-scale bound constrained optimization problems is developed. It is modifications of the subspace limited memory quasi-Newton method proposed by Ni and Yuan [Q. Ni, Y.X. Yuan, A subspace limited memory quasi-Newton algorithm for large-scale nonlinear bound constrained optimization, Math. Comput. 66 (1997) 1509-1520]. An important property of our proposed method is that more limited memory BFGS update is used. Under appropriate conditions, the global convergence of the method is established. The implementations of the method on CUTE test problems are presented, which indicate the modifications are beneficial to the performance of the algorithm.