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A feasible-direction method for nonlinear constrained optimization

✍ Scribed by Germana Landi

Publisher
Springer-Verlag
Year
2002
Tongue
German
Weight
835 KB
Volume
48
Category
Article
ISSN
0430-3202

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In this work, combining the properties of the generalized super-memory gradient projection methods with the ideas of the strongly sub-feasible directions methods, we present a new algorithm with strong convergence for nonlinear inequality constrained optimization. At each iteration, the proposed alg