A New Hyperplane Method for Solving Linear Inequality Constrained Optimization ⋆
نویسندگان
چکیده
For solving linear inequality constrained optimization, a new hyperplane method is introduced. The trust region approach for unconstraint optimization is used to minimize objective function on the hyperplane defined by the current iterative point. If a separate indicator shows that it is not worthwhile to find a better point in the current hyperplane. Then a line search along a chopped direction will be used. The proposed method can overcome the zigzagging phenomenons. Global convergence of the algorithm is proved. The numerical results are presented to show the property and efficiency of the proposed method.
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