Linear Programming

Linear Programming is a mathematical optimization technique that determines the best outcome in a given mathematical model characterized by linear relationships, specifically by maximizing or minimizing a linear objective function subject to a set of linear equality and inequality constraints.

14K

Publications

998.3K

Citations

18.1K

Authors

3.6K

Institutions

Publications per year

2017–2026

2.1K

Authors

18.1K

  1. OL
    O. L. Mangasarian

    University of Wisconsin–Madison, United States

    53 publications · 7.1K citations

    37

    h-index

  2. YY
    Yinyu Ye

    Stanford University, United States

    55 publications · 4.1K citations

    34

    h-index

  3. AC
    A. Charnes

    The University of Texas at Austin, United States

    53 publications · 10.7K citations

    34

    h-index

  4. MJ
    Michael J. Todd

    Cornell University, United States

    52 publications · 8.6K citations

    32

    h-index

  5. HD
    Hanif D. Sherali

    Virginia Tech, United States

    49 publications · 4.4K citations

    32

    h-index

1–5 of 18.1K

Venues

  1. Mathematical Programming

    718 publications · 70.9K citations

    129

    h-index

  2. Operations Research

    337 publications · 52.6K citations

    105

    h-index

  3. Management Science

    247 publications · 41.4K citations

    92

    h-index

  4. European Journal of Operational Research

    610 publications · 35.5K citations

    91

    h-index

  5. IEEE Transactions on Power Systems

    232 publications · 23.8K citations

    84

    h-index

1–5