Revisions of constraint approximations in the successive QP method for nonlinear programming problems
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Abstract
In the last few years the successive quadratic programming methods proposed by Han and Powell have been widely recognized as excellent means for solving nonlinea programming problems.
However, there remain some questions about their linear approximations to the constraints from both theoretical and empirical points of view.
In this paper, we propose two revisions of the linear approximation to the constraints and show that the directions generated by the revisions are also descent directions of exact penalty functions of nonlinear programming problems. The new technique can cope better with bad starting points than the usual one.
Key words
Nonlinear Programming Successive Quadratic Programming Method Linear Approximations Start Procedure Exact Penalty FunctionPreview
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References
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- [3]V.F. Dem'yanov and V.N. Malozemov,Introduction to minimax (John Wiley and Sons, New York, 1974).Google Scholar
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- [5]M.J.D. Powell, “A fast algorithm for nonlinearly constrained optimization calculus”,Proceedings of the 1977 Dundee Biennial Conference on Numerical Analysis (Springer-Verlag, Berlin, 1978).Google Scholar
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© North-Holland Publishing Company 1983