Dynamic Inventory Optimization

Dynamic Inventory Optimization is a mathematical modeling framework that distinguishes itself by enabling real-time, adaptive decision-making in multi-echelon inventory systems through the integration of stochastic demand forecasts, lead time dynamics, and network-level coordination to minimize total system costs under uncertainty.

123

Publications

13K

Citations

280

Authors

157

Institutions

Publications per year

2017–2026

36

Authors

280

  1. AF
    Arthur F. Veinott

    Stanford University, United States

    3 publications · 788 citations

    3

    h-index

  2. XG
    Xiting Gong

    Chinese University of Hong Kong, Hong Kong SAR China

    3 publications · 118 citations

    3

    h-index

  3. NY
    Nan Yang

    Washington University in St. Louis, United States

    3 publications · 112 citations

    3

    h-index

  4. RZ
    Renyu Zhang

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 62 citations

    2

    h-index

  5. SL
    Shudong Liu

    Agency for Science, Technology and Research, Singapore

    2 publications · 56 citations

    2

    h-index

1–5 of 280

Venues

  1. Management Science

    21 publications · 8.1K citations

    18

    h-index

  2. Production and Operations Management

    POMS · 7 publications · 252 citations

    7

    h-index

  3. Computers & Operations Research

    7 publications · 378 citations

    7

    h-index

  4. Computers & Industrial Engineering

    7 publications · 408 citations

    7

    h-index

  5. European Journal of Operational Research

    7 publications · 347 citations

    7

    h-index

1–5