Primal Linear Programming

Primal Linear Programming is a canonical optimization framework in linear programming that belongs to the class of mathematical programming models, distinguished by its formulation of a primary objective function and constraints aimed at maximizing or minimizing a linear function subject to linear equality and inequality constraints.

195

Publications

12K

Citations

321

Authors

160

Institutions

Publications per year

2017–2026

11

Authors

321

  1. MJ
    Michael J. Todd

    Cornell University, United States

    11 publications · 1.2K citations

    11

    h-index

  2. DF
    David F. Shanno

    Rutgers, The State University of New Jersey, United States

    9 publications · 1.3K citations

    9

    h-index

  3. IJ
    Irvin J. Lustig

    Princeton University, United States

    7 publications · 1.2K citations

    7

    h-index

  4. TT
    Tamás Terlaky

    Delft University of Technology, Netherlands

    7 publications · 395 citations

    7

    h-index

  5. YY
    Yinyu Ye

    Stanford University, United States

    7 publications · 1.1K citations

    7

    h-index

1–5 of 321

Venues

  1. SIAM Journal on Optimization

    15 publications · 775 citations

    14

    h-index

  2. Mathematical Programming

    15 publications · 1.6K citations

    14

    h-index

  3. Mathematics of Operations Research

    15 publications · 1.7K citations

    12

    h-index

  4. Annals of Operations Research

    8 publications · 397 citations

    8

    h-index

  5. Operations Research Letters

    6 publications · 301 citations

    6

    h-index

1–5