Bound Tightening

Bound Tightening is a deterministic preprocessing technique in global optimization that narrows the feasible domain of decision variables by iteratively updating their lower and upper bounds while preserving the location of global optima.

85

Publications

4.2K

Citations

202

Authors

139

Institutions

Publications per year

2017–2026

19

Authors

202

  1. KT
    Kunal Talwar

    Microsoft (United States), United States

    3 publications · 938 citations

    3

    h-index

  2. PM
    Pedro M. Castro

    University of Lisbon, Portugal

    3 publications · 257 citations

    3

    h-index

  3. JF
    Jittat Fakcharoenphol

    Kasetsart University, Thailand

    3 publications · 938 citations

    3

    h-index

  4. HN
    Harsha Nagarajan

    Los Alamos National Laboratory, United States

    2 publications · 32 citations

    2

    h-index

  5. AG
    Ambros Gleixner

    Zuse Institute Berlin, Germany

    2 publications · 289 citations

    2

    h-index

1–5 of 202

Venues

  1. IEEE Transactions on Power Systems

    6 publications · 362 citations

    6

    h-index

  2. Journal of Global Optimization

    5 publications · 181 citations

    5

    h-index

  3. INFORMS journal on computing

    5 publications · 219 citations

    5

    h-index

  4. Operations Research

    4 publications · 120 citations

    4

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 85 citations

    3

    h-index

1–5