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Barrier nonlinear programming (NLP) solvers exploit sparse Newton-based algorithms and are characterized by fast performance and global convergence properties. This makes them especially suitable for very large process optimization problems. On the other hand, they are frequently challenged by degenerate and indefinite problems, which lead to ill-conditioned Karush–Kuhn–Tucker (KKT) systems. Such...
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