An Improved Predictor-Corrector Interior-Point Algorithm for Linear Complementarity Problems with -Iteration Complexity | Zendy

Debin Fang | Zendy; Yu Qian | Zendy

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An Improved Predictor-Corrector Interior-Point Algorithm for Linear Complementarity Problems with -Iteration Complexity

Author(s) -

Debin Fang,

Yu Qian

Publication year - 2011

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2011/340192

Subject(s) - predictor–corrector method , interior point method , algorithm , complementarity (molecular biology) , mathematics , path (computing) , point (geometry) , convergence (economics) , mathematical optimization , computer science , programming language , economic growth , genetics , geometry , economics , biology

This paper proposes an improved predictor-corrector interior-point algorithm for the linear complementarity problem (LCP) based on the Mizuno-Todd-Ye algorithm. The modified corrector steps in our algorithm cannot only draw the iteration point back to a narrower neighborhood of the center path but also reduce the duality gap. It implies that the improved algorithm can converge faster than the MTY algorithm. The iteration complexity of the improved algorithm is proved to obtain √() which is similar to the classical Mizuno-Todd-Ye algorithm. Finally, the numerical experiments show that our algorithm improved the performance of the classical MTY algorithm

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