Convex Dynamic Optimization

Convex Dynamic Optimization is a dynamic optimization framework characterized by the property that the objective function and feasible set are convex at each stage, ensuring that local optima are global optima and enabling efficient solution via principled iterative algorithms.

67

Publications

2.7K

Citations

153

Authors

104

Institutions

Publications per year

2017–2026

24

Authors

153

  1. AR
    Alejandro Ribeiro

    University of Pennsylvania, United States

    4 publications · 226 citations

    4

    h-index

  2. QL
    Qing Ling

    University of Science and Technology of China, China

    3 publications · 199 citations

    3

    h-index

  3. XC
    Xuanyu Cao

    University of Illinois Urbana-Champaign, United States

    2 publications · 140 citations

    2

    h-index

  4. SH
    Sahar Harati

    Emory University, United States

    2 publications · 35 citations

    2

    h-index

  5. ZC
    Zaki Chbani

    Cadi Ayyad University, Morocco

    2 publications · 30 citations

    2

    h-index

1–5 of 153

Venues

  1. European Journal of Operational Research

    6 publications · 201 citations

    6

    h-index

  2. Computers & Chemical Engineering

    4 publications · 328 citations

    4

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 60 citations

    4

    h-index

  4. IEEE Transactions on Automatic Control

    3 publications · 224 citations

    3

    h-index

  5. 2

    h-index

1–5