Multiobjective Particle Swarm Optimization

Multiobjective Particle Swarm Optimization is a metaheuristic optimization algorithm that extends the basic Particle Swarm Optimization framework by incorporating mechanisms to simultaneously solve multiple conflicting objectives and maintain a set of nondominated solutions in the search space.

1.9K

Publications

93.8K

Citations

5.6K

Authors

1.6K

Institutions

Publications per year

2017–2026

1.1K

Variants

MopsoMulti-objective Particle Swarm Optimization

Authors

5.6K

  1. CA
    Carlos A. Coello Coello

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

    19 publications · 5.5K citations

    17

    h-index

  2. SM
    Sanaz Mostaghim

    Otto-von-Guericke-Universität Magdeburg, Germany

    13 publications · 1.3K citations

    12

    h-index

  3. AL
    Andrew Lewis

    Griffith University, Australia

    13 publications · 294 citations

    11

    h-index

  4. RT
    Reza Tavakkoli‐Moghaddam

    University of Tehran, Iran

    11 publications · 355 citations

    11

    h-index

  5. MR
    Masoud Rabbani

    University of Tehran, Iran

    11 publications · 471 citations

    10

    h-index

1–5 of 5.6K

Venues

  1. Applied Soft Computing

    36 publications · 3K citations

    32

    h-index

  2. IEEE Access

    66 publications · 3.3K citations

    32

    h-index

  3. Energies

    43 publications · 1.4K citations

    23

    h-index

  4. Sustainability

    25 publications · 862 citations

    19

    h-index

  5. IEEE Transactions on Magnetics

    22 publications · 1.1K citations

    19

    h-index

1–5