A Quadratically-Convergent Algorithm for General Nonlinear Programming Problems.
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WISCONSIN UNIV MADISON MATHEMATICS RESEARCH CENTER
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The paper presents an algorithm for solving nonlinearly constrained programming problems. The algorithm reduces the original problem to a sequence of linearly-constrained minimization problems, for which efficient algorithms are available. A convergence theorem is given which states that if the process is started sufficiently close to a strict second-order Kuhn-Tucker point, then the sequence produced by the algorithm exists and converges R-quadratically to that point. Author
- Operations Research