{"query_id":"27c052e1-436f-4580-8a83-f9cf1b442b7b","paper":{"id":"dd95519adf528fd234316f6d65ec1727d532ad97","title":"A Limited Memory Variable Metric Method in Subspaces and Bound Constrained Optimization Problems","venue":"in Subspaces and Bound Constrained Optimization Problems","year":"2001","publisher":null,"n_cited_by":0,"n_self_cites":0,"abstract":"We describe an algorithm for solving nonlinear optimization problems with lower  and upper bounds that constrain the variables. The algorithm uses projected gradients  to construct a limited memory BFGS matrix and determine a step direction. The  algorithm has been implemented and distributed as part of the Toolkit for Advanced  Optimization (TAO). We include numerical results demonstrate is eectiveness on a set  of large test problems and its scalability to multiple processors.","bibtex":"test_bibtex","authors":["Steven J. Benson","Jorge J. More"],"journal":null,"publish_time":"2001","source":"http://www-unix.mcs.anl.gov/~benson/blmvm/blmvm.ps","urls":[],"cluster_id":"i7hX1YMByhvPsGt1JYLB"}}