Parameter Uncertainty Optimization

Parameter Uncertainty Optimization is a methodological framework within optimization under uncertainty that specifically addresses the inherent variability and imprecision in model parameters by systematically incorporating probabilistic, interval-based, or scenario-driven representations of parameter uncertainty to yield robust or adaptive optimal solutions.

261

Publications

10.5K

Citations

757

Authors

330

Institutions

Publications per year

2017–2026

101

Authors

757

  1. GH
    Guohe Huang

    University of Regina, Canada

    17 publications · 903 citations

    14

    h-index

  2. YL
    Yongping Li

    University of Regina, Canada

    7 publications · 479 citations

    7

    h-index

  3. LH
    Li He

    North China Electric Power University, China

    6 publications · 158 citations

    6

    h-index

  4. VD
    Vivek Dua

    University College London, United Kingdom

    4 publications · 75 citations

    4

    h-index

  5. HL
    Hongwei Lu

    North China Electric Power University, China

    4 publications · 95 citations

    4

    h-index

1–5 of 757

Venues

  1. Industrial & Engineering Chemistry Research

    8 publications · 368 citations

    8

    h-index

  2. Computers & Chemical Engineering

    8 publications · 480 citations

    8

    h-index

  3. Engineering Optimization

    7 publications · 179 citations

    7

    h-index

  4. Energy

    7 publications · 245 citations

    7

    h-index

  5. AIChE Journal

    5 publications · 168 citations

    5

    h-index

1–5