Abstract
An improvement over an earlier feasible directions minimization algorithm is presented. In a certain sense the new feasible descent cone algorithm is shown to be a generalization of Rosen's gradient projection method. The algorithm is evaluated for linear programming test problems, and promising results are obtained for random problems and problems involving weight minimization of plane trusses.
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