Agent-based Optimization

Agent-Based Optimization is a computational methodology within agent-based design that leverages autonomous, interacting agents to explore and adaptively refine solutions in complex search spaces, distinguishing itself from conventional optimization techniques through decentralized decision-making and emergent coordination.

932

Publications

46.5K

Citations

2.5K

Authors

942

Institutions

Publications per year

2017–2026

295

Authors

2.5K

  1. SC
    Shu‐Heng Chen

    National Chengchi University, Taiwan

    8 publications · 511 citations

    7

    h-index

  2. SK
    Sven Koenig

    University of Southern California, United States

    6 publications · 341 citations

    6

    h-index

  3. MT
    Milind Tambe

    University of Southern California, United States

    6 publications · 391 citations

    6

    h-index

  4. NR
    Nicholas R. Jennings

    University of Southampton, United Kingdom

    5 publications · 548 citations

    6

    h-index

  5. MZ
    Mostafa Z. Ali

    Jordan University of Science and Technology, Jordan

    6 publications · 153 citations

    6

    h-index

1–5 of 2.5K

Venues

  1. Expert Systems with Applications

    13 publications · 381 citations

    12

    h-index

  2. Computers & Industrial Engineering

    13 publications · 651 citations

    12

    h-index

  3. arXiv (Cornell University)

    Repository · 12 publications · 317 citations

    12

    h-index

  4. Applied Energy

    11 publications · 878 citations

    12

    h-index

  5. European Journal of Operational Research

    10 publications · 644 citations

    10

    h-index

1–5