Approximation Algorithms For Coloring

Approximation Algorithms for Coloring is an algorithmic framework in computational combinatorics that belongs to the class of heuristic methods for NP-hard graph problems and specifically addresses graph coloring by computing near-optimal colorings with provable performance guarantees relative to the chromatic number.

706

Publications

26.4K

Citations

1.1K

Authors

526

Institutions

Publications per year

2017–2026

70

Authors

1.1K

  1. AK
    Alexandr Kostochka

    University of Illinois Urbana-Champaign, United States

    14 publications · 520 citations

    13

    h-index

  2. AH
    Alain Hertz

    École Polytechnique Fédérale de Lausanne, Switzerland

    10 publications · 708 citations

    10

    h-index

  3. OV
    O. V. Borodin

    Sobolev Institute of Mathematics, Russia

    9 publications · 370 citations

    9

    h-index

  4. AR
    André Raspaud

    Laboratoire Bordelais de Recherche en Informatique, France

    9 publications · 244 citations

    9

    h-index

  5. XZ
    Xuding Zhu

    National Sun Yat-sen University, Taiwan

    9 publications · 419 citations

    9

    h-index

1–5 of 1.1K

Venues

  1. Discrete Mathematics

    114 publications · 3.6K citations

    31

    h-index

  2. Journal of Combinatorial Theory Series B

    46 publications · 2.3K citations

    28

    h-index

  3. Discrete Applied Mathematics

    63 publications · 2.1K citations

    25

    h-index

  4. Information Processing Letters

    25 publications · 1.2K citations

    18

    h-index

  5. COMBINATORICA

    25 publications · 1.1K citations

    17

    h-index

1–5