Stochastic Global Optimization

Stochastic Global Optimization is a global optimization method that incorporates randomization in its search process to explore the solution space and escape local optima, thereby increasing the likelihood of converging to the global optimum in complex, multimodal landscapes.

241

Publications

16.2K

Citations

544

Authors

283

Institutions

Publications per year

2017–2026

42

Authors

544

  1. AH
    A. H. G. Rinnooy Kan

    Erasmus University Rotterdam, Netherlands

    7 publications · 1.3K citations

    7

    h-index

  2. CS
    Cheng Shang

    Fudan University, China

    6 publications · 576 citations

    6

    h-index

  3. AB
    Adrián Bonilla‐Petriciolet

    Universidad Tecnológica de Aguascalientes, Mexico

    6 publications · 179 citations

    6

    h-index

  4. ZL
    Zhi‐Pan Liu

    Fudan University, China

    6 publications · 576 citations

    6

    h-index

  5. GP
    Gade Pandu Rangaiah

    National University of Singapore, Singapore

    5 publications · 175 citations

    5

    h-index

1–5 of 544

Venues

  1. Journal of Global Optimization

    14 publications · 2.1K citations

    12

    h-index

  2. Industrial & Engineering Chemistry Research

    7 publications · 276 citations

    7

    h-index

  3. Computers & Chemical Engineering

    6 publications · 578 citations

    6

    h-index

  4. Mathematical Programming

    5 publications · 1.5K citations

    5

    h-index

  5. SIAM Journal on Control and Optimization

    5 publications · 739 citations

    5

    h-index

1–5