Layout Optimization Under Uncertainty

Layout Optimization Under Uncertainty is a computational framework within layout optimization that explicitly accounts for unpredictable variations in input parameters, spatial demands, or operational conditions by integrating stochastic, fuzzy, or robust optimization techniques to produce resilient and adaptive spatial configurations.

59

Publications

2.3K

Citations

162

Authors

86

Institutions

Publications per year

2017–2026

20

Authors

162

  1. KK
    Krishna K. Krishnan

    Wichita State University, United States

    3 publications · 167 citations

    3

    h-index

  2. KE
    Kourosh Eshghi

    Sharif University of Technology, Iran

    3 publications · 107 citations

    3

    h-index

  3. JZ
    Jihong Zhu

    Northwestern Polytechnical University, China

    2 publications · 79 citations

    2

    h-index

  4. MH
    Mohammad Hassan Salmani

    Sharif University of Technology, Iran

    2 publications · 61 citations

    2

    h-index

  5. JA
    Jinyu An

    Guizhou University, China

    2 publications · 33 citations

    2

    h-index

1–5 of 162

Venues

  1. International Journal of Production Research

    4 publications · 274 citations

    4

    h-index

  2. Computers & Industrial Engineering

    3 publications · 182 citations

    3

    h-index

  3. 3

    h-index

  4. Expert Systems with Applications

    3 publications · 146 citations

    3

    h-index

  5. Renewable Energy

    2 publications · 75 citations

    2

    h-index

1–5