Abstract
For solving nonlinear constrained optimization problems the reduced gradient method is used. The computation of the descent directions is performed similar to the way applied for linear constraints. Contrary to the method of Abadie/Carpentier, in every iteration point the obtained direction is not only a descent direction but also a feasible direction.

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