Online Knapsack

Online Knapsack is an online optimization problem in which items arrive sequentially and must be irrevocably accepted or rejected upon arrival, aiming to maximize the total value of selected items without exceeding a fixed capacity, distinguishing it from offline knapsack variants by the absence of future item information and the requirement for immediate decision-making.

53

Publications

5.6K

Citations

124

Authors

86

Institutions

Publications per year

2017–2026

23

Variants

Online Knapsack Problem

Authors

124

  1. XH
    Xin Han

    Dalian University of Technology, China

    5 publications · 128 citations

    5

    h-index

  2. BS
    Bo Sun

    Hong Kong University of Science and Technology, Hong Kong SAR China

    5 publications · 101 citations

    5

    h-index

  3. KM
    Kazuhisa Makino

    Kyoto University, Japan

    5 publications · 128 citations

    5

    h-index

  4. MH
    Mohammad Hajiesmaili

    University of Massachusetts Amherst, United States

    4 publications · 89 citations

    4

    h-index

  5. AW
    Adam Wierman

    California Institute of Technology, United States

    4 publications · 89 citations

    4

    h-index

1–5 of 124

Venues

  1. Theoretical Computer Science

    6 publications · 167 citations

    6

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 57 citations

    3

    h-index

  3. Algorithmica

    2 publications · 49 citations

    2

    h-index

  4. Journal of the Operational Research Society

    OR · 2 publications · 3.8K citations

    2

    h-index

  5. 2

    h-index

1–5