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Weighted-path-following interior-point algorithm to monotone mixed linear complementarity problem

Author

Listed:
  • Guo-qiang Wang

    (Shanghai University of Engineering Science)

  • Yu-jing Yue

    (Shanghai University of Engineering Science)

  • Xin-zhong Cai

    (Shanghai University of Engineering Science)

Abstract

In this paper we propose a weighted-path-following interior-point algorithm to monotone mixed linear complementarity problem. The algorithm is based on a new technique for finding a class of search directions and the strategy of the central path. At each iteration, we only use full-Newton step. Finally, the currently best known iteration bound for the algorithm with a small-update method, namely, O(√nlog n/ε) is derived, which is as good as the bound for the linear optimization analogue.

Suggested Citation

  • Guo-qiang Wang & Yu-jing Yue & Xin-zhong Cai, 2009. "Weighted-path-following interior-point algorithm to monotone mixed linear complementarity problem," Fuzzy Information and Engineering, Springer, vol. 1(4), pages 435-445, December.
    • Handle: RePEc:spr:fuzinf:v:1:y:2009:i:4:d:10.1007_s12543-009-0033-x
    DOI: 10.1007/s12543-009-0033-x
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    References listed on IDEAS

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    1. M. Seetharama Gowda & Jong-Shi Pang, 1992. "On Solution Stability of the Linear Complementarity Problem," Mathematics of Operations Research, INFORMS, vol. 17(1), pages 77-83, February.
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    Cited by:

    1. Zs. Darvay & T. Illés & B. Kheirfam & P. R. Rigó, 2020. "A corrector–predictor interior-point method with new search direction for linear optimization," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(3), pages 1123-1140, September.

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