Multi-objective Evolutionary Architecture

Multi-Objective Evolutionary Architecture is an evolutionary architecture approach that integrates multiple competing objectives—such as performance, reliability, and cost—into the continuous adaptation and optimization of software systems, distinguishing itself by employing search-based techniques to evolve architectural configurations that achieve balanced trade-offs across these objectives.

26

Publications

1.4K

Citations

106

Authors

46

Institutions

Publications per year

2017–2026

14

Authors

106

  1. FM
    Francesco Marcelloni

    University of Pisa, Italy

    1 publications · 38 citations

    1

    h-index

  2. HB
    Hossein Bonakdari

    Razi University, Iran

    1 publications · 49 citations

    1

    h-index

  3. AJ
    Adnan J. Jabir

    University of Baghdad, Iraq

    1 publications · 13 citations

    1

    h-index

  4. SW
    Song Wang

    La Trobe University, Australia

    1 publications · 34 citations

    1

    h-index

  5. JZ
    Jianwei Zhang

    Sichuan University, China

    1 publications · 20 citations

    1

    h-index

1–5 of 106

Venues

  1. Applied Soft Computing

    4 publications · 125 citations

    3

    h-index

  2. Expert Systems with Applications

    2 publications · 58 citations

    2

    h-index

  3. 1

    h-index

  4. IEEE Transactions on Neural Networks

    1 publications · 38 citations

    1

    h-index

  5. Information Sciences

    1 publications · 50 citations

    1

    h-index

1–5