Linear Programming Relaxations

Linear Programming Relaxation is a mathematical optimization technique that belongs to the class of relaxation methods, distinguished by its transformation of an integer programming problem into a linear programming problem through the removal of integrality constraints on the variables.

1.1K

Publications

90.3K

Citations

1.9K

Authors

727

Institutions

Publications per year

2017–2026

141

Authors

1.9K

  1. HD
    Hanif D. Sherali

    Virginia Tech, United States

    14 publications · 2K citations

    14

    h-index

  2. WP
    Warren P. Adams

    Clemson University, United States

    9 publications · 1.9K citations

    9

    h-index

  3. LA
    Laurence A. Wolsey

    UCLouvain, Belgium

    7 publications · 430 citations

    7

    h-index

  4. JB
    Jean B. Lasserre

    Laboratoire d'Analyse et d'Architecture des Systèmes, France

    7 publications · 855 citations

    7

    h-index

  5. SI
    Saul I. Gass

    University of Maryland, College Park, United States

    7 publications · 725 citations

    7

    h-index

1–5 of 1.9K

Venues

  1. Mathematical Programming

    81 publications · 8.5K citations

    40

    h-index

  2. Operations Research

    32 publications · 4.9K citations

    27

    h-index

  3. European Journal of Operational Research

    46 publications · 2.8K citations

    26

    h-index

  4. Journal of the Operational Research Society

    OR · 31 publications · 11.3K citations

    20

    h-index

  5. Operations Research Letters

    32 publications · 1.2K citations

    19

    h-index

1–5