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A relaxed primal-dual path-following algorithm for linear programming

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Abstract

In this paper, we provide an easily satisfied relaxation condition for the primaldual interior path-following algorithm to solve linear programming problems. It is shown that the relaxed algorithm preserves the property of polynomial-time convergence. The computational results obtained by implementing two versions of the relaxed algorithm with slight modifications clearly demonstrate the potential in reducing computational efforts.

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Authors and Affiliations

  1. Institute of Applied Mathematics, National Tsing Hua University, 30043, Hsinchu, Taiwan R.O.C.

    Tsung-Min Hwang, Chih-Hung Lin & Wen-Wei Lin

  2. Operations Research and Industrial Engineering, North Carolina State University, 27615-7913, Raleigh, NC, USA

    Shu-Cherng Fang

Authors
  1. Tsung-Min Hwang
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  2. Chih-Hung Lin
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  3. Wen-Wei Lin
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  4. Shu-Cherng Fang
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Additional information

Partially supported by the North Carolina Supercomputing Center, the 1993 Cray Research Award, and a National Science Council Research Grant of the Republic of China.

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Hwang, TM., Lin, CH., Lin, WW. et al. A relaxed primal-dual path-following algorithm for linear programming. Ann Oper Res 62, 173–196 (1996). https://doi.org/10.1007/BF02206816

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