Greedy Algorithms

Greedy Algorithms is a class of algorithmic design strategies that constructs a solution by making a sequence of locally optimal choices at each step, hoping to achieve a globally optimal solution, distinguishing it from other algorithmic paradigms that may delay or reconsider decisions.

1.7K

Publications

110.6K

Citations

3.3K

Authors

1.1K

Institutions

Publications per year

2017–2026

468

Authors

3.3K

  1. VT
    Vladimir Temlyakov

    University of South Carolina, United States

    30 publications · 1.8K citations

    19

    h-index

  2. QP
    Quan-Ke Pan

    Liaocheng University, China

    21 publications · 1.8K citations

    19

    h-index

  3. AK
    Andreas Krause

    ETH Zurich, Switzerland

    15 publications · 1.6K citations

    15

    h-index

  4. LG
    Liang Gao

    Huazhong University of Science and Technology, China

    14 publications · 945 citations

    14

    h-index

  5. FA
    Fernando Albiac

    Universidad Pública de Navarra (UPNA), Spain

    13 publications · 285 citations

    12

    h-index

1–5 of 3.3K

Venues

  1. arXiv (Cornell University)

    Repository · 86 publications · 4.3K citations

    30

    h-index

  2. Information Processing Letters

    27 publications · 1.3K citations

    20

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 28 publications · 1.6K citations

    18

    h-index

  4. European Journal of Operational Research

    21 publications · 2.9K citations

    18

    h-index

  5. Expert Systems with Applications

    20 publications · 1.2K citations

    18

    h-index

1–5