A solver of large-scale unconstrained minimization problems.
The routine M1QN3 has been designed to minimize functions depending on a very large number of variables (several hundred million is sometimes possible) not subject to constraints. It implements a limited memory quasi-Newton technique (the L-BFGS method of J. Nocedal) with a dynamically updated scalar or diagonal preconditioner. It uses line-search to enforce global convergence; more precisely, the step-size is determined by the Fletcher-LemarÃÂ©chal algorithm and realizes the Wolfe conditions.
released on 14 January 2009
14 January 2009
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This entry (in part or in whole) was last reviewed on 14 February 2017.
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