Sequential Convex Optimization

Sequential Convex Optimization is an iterative numerical optimization technique that approximates a non-convex optimization problem by a sequence of convex subproblems, each constructed to locally approximate the original problem’s objective and constraints, thereby enabling efficient convergence to a stationary solution through successive refinement.

319

Publications

21.5K

Citations

803

Authors

324

Institutions

Publications per year

2017–2026

162

Variants

Successive Convex Optimization

Authors

803

  1. MD
    Moritz Diehl

    KU Leuven, Belgium

    10 publications · 398 citations

    10

    h-index

  2. SC
    Soon‐Jo Chung

    University of Illinois Urbana-Champaign, United States

    9 publications · 740 citations

    9

    h-index

  3. AM
    A. Miele

    Rice University, United States

    8 publications · 535 citations

    8

    h-index

  4. FY
    Fred Y. Hadaegh

    Jet Propulsion Laboratory, United States

    8 publications · 723 citations

    8

    h-index

  5. HC
    Haotong Cao

    Nanjing University of Posts and Telecommunications, China

    5 publications · 180 citations

    5

    h-index

1–5 of 803

Venues

  1. IEEE Transactions on Vehicular Technology

    13 publications · 582 citations

    12

    h-index

  2. arXiv (Cornell University)

    Repository · 8 publications · 259 citations

    8

    h-index

  3. IEEE Transactions on Communications

    8 publications · 862 citations

    8

    h-index

  4. 8

    h-index

  5. IEEE Access

    8 publications · 327 citations

    8

    h-index

1–5