SLMQN: A Fortran code of subspace limited memory quasi-Newton method for large-scale bound constrained nonlinear optimization. SLMQN is a subspace limited memory quasi-Newton algorithm for solving large-scale bound constrained nonlinear programming problems. The algorithm is suitable to those large problems in which the Hessian matrix is difficult to compute or is dense, or the number of variables is too large to store and compute an $n imes n$ matrix. Due to less storage requirement, this algorithm can be used in PCs for solving medium-sized and large problems. The algorithm is implemented in Fortran 77.
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References in zbMATH (referenced in 2 articles , 1 standard article )
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- Tang, Mingyun: Trust region algorithm with two subproblems for bound constrained problems (2014)
- Ni, Q.; Yuan, Y.: SLMQN: A Fortran code of subspace limited memory quasi-Newton method for large-scale bound constrained nonlinear optimization (1997)