Feasibility Pumping

Feasibility Pumping is a heuristic algorithmic framework in mathematical optimization that iteratively refines solutions by alternating between rounding fractional solutions to integer values and projecting infeasible solutions onto the feasible set to drive convergence toward a feasible solution of mixed-integer programming problems.

14

Publications

871

Citations

33

Authors

19

Institutions

Publications per year

2017–2026

5

Authors

33

  1. TB
    Timo Berthold

    Zuse Institute Berlin, Germany

    4 publications · 368 citations

    4

    h-index

  2. AL
    Andrea Lodi

    University of Bologna, Italy

    3 publications · 294 citations

    3

    h-index

  3. AE
    Andrew Eberhard

    RMIT University, Australia

    2 publications · 54 citations

    2

    h-index

  4. AT
    Angelos Tsoukalas

    Imperial College London, United Kingdom

    2 publications · 54 citations

    2

    h-index

  5. NB
    Natashia Boland

    Georgia Institute of Technology, United States

    2 publications · 54 citations

    2

    h-index

1–5 of 33

Venues

  1. SIAM Journal on Optimization

    2 publications · 68 citations

    2

    h-index

  2. Discrete Optimization

    2 publications · 322 citations

    2

    h-index

  3. Mathematical Programming Computation

    1 publications · 30 citations

    1

    h-index

  4. EURO Journal on Computational Optimization

    1 publications · 25 citations

    1

    h-index

  5. Optimization methods & software

    1 publications · 32 citations

    1

    h-index

1–5