A Kind of NLP Algorithm with NCP Function
2011 ◽
Vol 467-469
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pp. 877-881
Keyword(s):
In this paper, two modifications are proposed for minimizing the nonlinear optimization problem (NLP) based on Fletcher and Leyffer’s filter method which is different from traditional merit function with penalty term. We firstly modify one component of filter pairs with NCP function instead of violation constrained function in order to avoid the difficulty of selecting penalty parameters. We also proved that the modified algorithm is globally and super linearly convergent under certain conditions. We secondly convert objective function to augmented Lagrangian function in case of incompatibility caused by sub-problems.
2010 ◽
Vol 121-122
◽
pp. 123-127
1995 ◽
Vol 142
(1)
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pp. 33
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2005 ◽
Vol 26
(12)
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pp. 1649-1656
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2015 ◽
Vol 13
(10)
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pp. 3277-3286
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1994 ◽
Vol 30
(1)
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pp. 88-96
2005 ◽
Vol 27
(7)
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pp. 528-532
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