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A new least square algorithm for linear programming

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Abstract

By attacking the linear programming problems from their dual side, a new general algorithm for linear programming is developed. At each iteration, the algorithm finds a feasible descent search direction by handling a least square problem associated with the dual system, using QR decomposition technique. The new method is a combination of pivot method and interior-point method. It in fact not only reduces the possibility of difficulty arising from degeneracy, but also has the same advantages as pivot method in warm-start to resolve linear programming problems. Numerical results of a group of randomly constructed problems are very encouraging.

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Authors and Affiliations

  1. School of Science, Hangzhou University of Electronic Technology, 310037, Hangzhou, China

    Li Wei & Chen Guangting

Authors
  1. Li Wei
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  2. Chen Guangting
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Additional information

Supported by the National Natural Science Foundation of China (10371028), Science Foundation of Zhejiang Bureau of Education (20030622) and Science Foundation of Hangzhou University of Electronic Technology (KYS091504025).

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Wei, L., Guangting, C. A new least square algorithm for linear programming. Appl. Math.- J. Chin. Univ. 21, 214–222 (2006). https://doi.org/10.1007/BF02791347

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  • DOI: https://doi.org/10.1007/BF02791347

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