Randomized Search Algorithms

Randomized Search Algorithms is a computational method that belongs to the class of search algorithms, distinguished by its use of randomness as an intrinsic component to guide the exploration of the solution space in order to improve efficiency or avoid local optima.

182

Publications

18.4K

Citations

404

Authors

217

Institutions

Publications per year

2017–2026

30

Authors

404

  1. CW
    Carsten Witt

    Technical University of Denmark, Denmark

    10 publications · 748 citations

    10

    h-index

  2. FN
    Frank Neumann

    The University of Adelaide, Australia

    7 publications · 177 citations

    7

    h-index

  3. CP
    Carla P. Gomes

    Cornell University, United States

    4 publications · 649 citations

    4

    h-index

  4. MK
    Ming‐Yang Kao

    Duke University, United States

    4 publications · 300 citations

    4

    h-index

  5. TJ
    Thomas Jansen

    TU Dortmund University, Germany

    4 publications · 246 citations

    4

    h-index

1–5 of 404

Venues

  1. Algorithmica

    8 publications · 583 citations

    8

    h-index

  2. Operations Research

    4 publications · 940 citations

    4

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 70 citations

    4

    h-index

  4. Theoretical Computer Science

    4 publications · 303 citations

    4

    h-index

  5. Proceedings of the Genetic and Evolutionary Computation Conference

    Conference · 4 publications · 119 citations

    4

    h-index

1–5