Large-scale Linear Programming

Large-Scale Linear Programming is a specialized form of mathematical optimization within linear programming that addresses problems involving a vast number of decision variables and constraints, distinguished by the computational and algorithmic challenges arising from the problem's high dimensionality and sparsity structure.

232

Publications

16.7K

Citations

457

Authors

235

Institutions

Publications per year

2017–2026

38

Authors

457

  1. JG
    Jacek Gondzio

    University of Edinburgh, United Kingdom

    8 publications · 466 citations

    8

    h-index

  2. KT
    Kim-Chuan Toh

    National University of Singapore, Singapore

    5 publications · 205 citations

    5

    h-index

  3. DS
    Defeng Sun

    National University of Singapore, Singapore

    5 publications · 205 citations

    5

    h-index

  4. MA
    Michael A. Saunders

    Stanford University, United States

    4 publications · 659 citations

    4

    h-index

  5. AR
    Andrzej Ruszczyński

    Rutgers, The State University of New Jersey, United States

    4 publications · 201 citations

    4

    h-index

1–5 of 457

Venues

  1. Mathematical Programming

    15 publications · 1.6K citations

    14

    h-index

  2. Operations Research

    13 publications · 5K citations

    13

    h-index

  3. Management Science

    11 publications · 1.4K citations

    11

    h-index

  4. SIAM Journal on Optimization

    6 publications · 315 citations

    7

    h-index

  5. Annals of Operations Research

    5 publications · 114 citations

    6

    h-index

1–5