A dual differentiable exact penalty function |
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Authors: | S -P Han O L Mangasarian |
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Institution: | (1) University of Illinois, Urbana, IL, U.S.A.;(2) University of Wisconsin, Madison, WI, U.S.A. |
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Abstract: | A new penalty function is associated with an inequality constrained nonlinear programming problem via its dual. This penalty
function is globally differentiable if the functions defining the original problem are twice globally differentiable. In addition,
the penalty parameter remains finite. This approach reduces the original problem to a simple problem of maximizing a globally
differentiable function on the product space of a Euclidean space and the nonnegative orthant of another Euclidean space.
Many efficient algorithms exist for solving this problem. For the case of quadratic programming, the penalty function problem
can be solved effectively by successive overrelaxation (SOR) methods which can handle huge problems while preserving sparsity
features.
Sponsored by the United States Army under Contract No. DAAG 29-80-C-0041. This material is based upon work supported by the
National Science Foundation under Grants No. MCS-790166 and ENG-7903881. |
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Keywords: | Nonlinear Programming Quadratic Programming Penalty Functions SOR Methods |
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