Randomized Packing Algorithms

Randomized Packing Algorithms is a class of algorithmic methods in computational geometry that employs randomization to efficiently construct or approximate arrangements of geometric objects within a given space, distinguishing itself by leveraging probabilistic strategies to achieve improved performance or simplicity in packing configurations compared to deterministic counterparts.

78

Publications

3.4K

Citations

174

Authors

111

Institutions

Publications per year

2017–2026

8

Authors

174

  1. ZC
    Zhi‐Zhong Chen

    Tokyo Denki University, Japan

    3 publications · 52 citations

    3

    h-index

  2. JC
    Jianer Chen

    Texas A&M University, United States

    3 publications · 118 citations

    3

    h-index

  3. TH
    Thore Husfeldt

    Lund University, Sweden

    2 publications · 120 citations

    2

    h-index

  4. RT
    Ruka Tanahashi

    Tokyo Denki University, Japan

    2 publications · 42 citations

    2

    h-index

  5. LW
    Lusheng Wang

    City University of Hong Kong, Hong Kong SAR China

    2 publications · 36 citations

    2

    h-index

1–5 of 174

Venues

  1. Algorithmica

    7 publications · 282 citations

    7

    h-index

  2. Information Processing Letters

    6 publications · 207 citations

    6

    h-index

  3. Discrete Mathematics

    6 publications · 170 citations

    6

    h-index

  4. Discrete & Computational Geometry

    3 publications · 51 citations

    3

    h-index

  5. Journal of Combinatorial Optimization

    3 publications · 50 citations

    3

    h-index

1–5