Abstract
This paper presents some more numerical experiments with LSNNO, a new FORTRAN subroutine for solving large-scale nonlinear network optimization problems. The implemented algorithm applies the concepts of partial separability and partitioned quasi-Newton updating to high-dimensional nonlinear network optimization problems. The experiments reported involve both academic and practical problems.
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