Monday, 15:45 - 16:10 h, Room: H 2035


Boshi Tian
An interior-point l1/2-penalty method for nonlinear programming

Coauthor: Xiaoqi Yang


In this presentation, we solve general nonlinear programming problems by using a quadratic relaxation scheme for their l1/2-lower order penalty problems.
Combining an interior point method, we propose an interior point l1/2-penalty function method, and design some robust algorithms. Using some relaxed constraint qualifications, we obtain first-order optimality conditions of relaxed l1/2-lower order penalty problems. We also carry out numerical experiments for three test problem sets, which contain small scale and medium scale test problems, large scale test problems and optimization problems with different kinds of degenerate constraints, respectively. The comparison of the numerical performance of our method with other existing interior point penalty methods shows that our method in general performs better in terms of CPU time, iteration number, barrier parameter, and penalty parameter.


Talk 2 of the invited session Mon.3.H 2035
"Lower order exact penalty functions" [...]
Cluster 24
"Variational analysis" [...]


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