Multi-objective Combinatorial Optimization

Multi-Objective Combinatorial Optimization is a subfield of mathematical optimization that addresses decision-making problems involving the simultaneous optimization of multiple conflicting objectives over discrete solution spaces, where solutions are typically characterized by combinatorial structures such as permutations, subsets, or graphs.

992

Publications

57.2K

Citations

2.4K

Authors

1K

Institutions

Publications per year

2017–2026

404

Variants

Moco

Authors

2.4K

  1. JR
    José Rui Figueira

    University of Lisbon, Portugal

    14 publications · 407 citations

    13

    h-index

  2. ME
    Matthias Ehrgott

    University of Auckland, New Zealand

    12 publications · 1.5K citations

    12

    h-index

  3. CA
    Carlos A. Coello Coello

    Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico

    11 publications · 300 citations

    11

    h-index

  4. MK
    Murat Köksalan

    Middle East Technical University, Türkiye

    11 publications · 395 citations

    11

    h-index

  5. SM
    Seyedali Mirjalili

    Torrens University Australia, Australia

    10 publications · 3.4K citations

    10

    h-index

1–5 of 2.4K

Venues

  1. European Journal of Operational Research

    46 publications · 3.7K citations

    30

    h-index

  2. Applied Soft Computing

    34 publications · 2.1K citations

    24

    h-index

  3. Computers & Operations Research

    28 publications · 1.4K citations

    22

    h-index

  4. Expert Systems with Applications

    27 publications · 1.4K citations

    22

    h-index

  5. Swarm and Evolutionary Computation

    19 publications · 1.3K citations

    17

    h-index

1–5