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

An active set limited memory BFGS algorithm for large-scale bound constrained optimization is introduced. The active sets are based on guessing technique to be identified at each iteration, the search direction in free subspace is determined by limited memory BFGS (L-BFGS) algorithm, which provides an efficient means for attacking large-scale optimization problems. The implementations of the method on CUTE test problems are described.