Heuristic Bounds

Heuristic Bounds is a bounding technique in branch and bound algorithms that belongs to the class of estimation methods used to approximate optimal solutions, distinguished by its reliance on heuristic rules to compute bounds that are computationally efficient yet potentially less tight than exact methods.

37

Publications

1.3K

Citations

80

Authors

51

Institutions

Publications per year

2017–2026

3

Authors

80

  1. CR
    Christophe Rapine

    Université de Lorraine, France

    1 publications · 12 citations

    1

    h-index

  2. GR
    Gabriel Robins

    University of Virginia, United States

    1 publications · 24 citations

    1

    h-index

  3. TM
    Thomas M. Liggett

    University of California, Los Angeles, United States

    1 publications · 48 citations

    1

    h-index

  4. JS
    Jadranka Skorin‐Kapov

    Stony Brook University, United States

    1 publications · 90 citations

    1

    h-index

  5. AM
    Abheejeet Mohapatra

    Indian Institute of Technology Kanpur, India

    1 publications · 40 citations

    1

    h-index

1–5 of 80

Venues

  1. European Journal of Operational Research

    4 publications · 135 citations

    4

    h-index

  2. Operations Research

    4 publications · 147 citations

    4

    h-index

  3. Management Science

    2 publications · 137 citations

    2

    h-index

  4. Naval Research Logistics (NRL)

    2 publications · 65 citations

    2

    h-index

  5. Information Processing Letters

    2 publications · 53 citations

    2

    h-index

1–5