Randomized Search

Randomized Search is a metaheuristic optimization method that belongs to the class of stochastic search algorithms, distinguished by its use of random sampling of parameter values from predefined distributions to explore the search space without relying on gradient information or deterministic rules.

310

Publications

34.4K

Citations

658

Authors

316

Institutions

Publications per year

2017–2026

61

Authors

658

  1. CW
    Carsten Witt

    Technical University of Denmark, Denmark

    14 publications · 956 citations

    14

    h-index

  2. FN
    Frank Neumann

    The University of Adelaide, Australia

    13 publications · 645 citations

    12

    h-index

  3. TJ
    Thomas Jansen

    TU Dortmund University, Germany

    7 publications · 350 citations

    7

    h-index

  4. MG
    Maurício G. C. Resende

    AT&T (United States), United States

    7 publications · 3.3K citations

    7

    h-index

  5. CZ
    Christine Zarges

    Aberystwyth University, United Kingdom

    5 publications · 198 citations

    5

    h-index

1–5 of 658

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 2K citations

    12

    h-index

  2. Algorithmica

    8 publications · 594 citations

    8

    h-index

  3. Theoretical Computer Science

    6 publications · 570 citations

    6

    h-index

  4. Evolutionary Computation

    6 publications · 208 citations

    6

    h-index

  5. SIAM Journal on Computing

    6 publications · 409 citations

    6

    h-index

1–5