Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
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A SUPERLINEAR $\mathcal{VU}$ SPACE-DECOMPOSITION ALGORITHM FOR SEMI-INFINITE CONSTRAINED PROGRAMMING

  • Huang, Ming (Institute of Operations Research and Control, School of Mathematical Sciences, (DUT)) ;
  • Pang, Li-Ping (Institute of Operations Research and Control, School of Mathematical Sciences, (DUT)) ;
  • Lu, Yuan (School of Sciences, Shenyang University) ;
  • Xia, Zun-Quan (Institute of Operations Research and Control, School of Mathematical Sciences, (DUT))
  • Received : 2011.04.15
  • Accepted : 2011.11.05
  • Published : 2012.09.30
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Abstract

In this paper, semi-infinite constrained programming, a class of constrained nonsmooth optimization problems, are transformed into unconstrained nonsmooth convex programs under the help of exact penalty function. The unconstrained objective function which owns the primal-dual gradient structure has connection with $\mathcal{VU}$-space decomposition. Then a $\mathcal{VU}$-space decomposition method can be applied for solving this unconstrained programs. Finally, the superlinear convergence algorithm is proved under certain assumption.

Keywords

Acknowledgement

Supported by : Natural Science Foundation of China

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