Constraint-based Optimization

Constraint-Based Optimization is a mathematical optimization approach that identifies optimal solutions within a feasible region defined by a set of equality and inequality constraints, distinguishing itself from unconstrained methods by explicitly incorporating domain-specific limitations into the optimization process.

977

Publications

56.7K

Citations

2.2K

Authors

932

Institutions

Publications per year

2017–2026

183

Authors

2.2K

  1. PV
    Pascal Van Hentenryck

    Brown University, United States

    9 publications · 263 citations

    9

    h-index

  2. EP
    E. Polak

    University of California, Berkeley, United States

    7 publications · 434 citations

    7

    h-index

  3. GD
    Gianni Di Pillo

    Sapienza University of Rome, Italy

    6 publications · 284 citations

    6

    h-index

  4. KD
    Kalyanmoy Deb

    Michigan State University, United States

    6 publications · 582 citations

    6

    h-index

  5. LM
    Laurent Michel

    University of Connecticut, United States

    5 publications · 126 citations

    5

    h-index

1–5 of 2.2K

Venues

  1. Mathematical Programming

    38 publications · 2.5K citations

    28

    h-index

  2. Journal of Optimization Theory and Applications

    32 publications · 860 citations

    20

    h-index

  3. Journal of Global Optimization

    28 publications · 734 citations

    18

    h-index

  4. SIAM Journal on Optimization

    14 publications · 442 citations

    13

    h-index

  5. Constraints

    15 publications · 635 citations

    13

    h-index

1–5