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An Arc Method for Nonlinear Programming.
GEORGE WASHINGTON UNIV WASHINGTON D C INST FOR MANAGEMENT SCIENCE AND ENGINEERING
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An algorithm using second derivatives for solving the optimization problem minimize fx subject to g subi x or 0, i 1,...,m where the g sub i are not necessarily linear is presented. The basic idea is to generate a sequence of feasible points with decreasing objective values by movement along piecewise, smooth, quadratic arcs. Cluster points of the sequence generated are shown to be second-order Kuhn-Tucker points. If the strict second order sufficiency conditions hold the rate of convergence is shown to be at least quadratic. Author
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