Multi-objective Task Allocation

Multi-Objective Task Allocation is a task allocation approach that belongs to the class of optimization methods in which the assignment of tasks to agents is governed by the simultaneous minimization or maximization of multiple conflicting objectives, distinguished from single-objective variants by its explicit consideration of trade-offs among diverse performance criteria.

70

Publications

3.4K

Citations

261

Authors

136

Institutions

Publications per year

2017–2026

51

Authors

261

  1. IG
    Irene Granata

    University of Padua, Italy

    2 publications · 74 citations

    2

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  2. MF
    Maurizio Faccio

    University of Padua, Italy

    2 publications · 74 citations

    2

    h-index

  3. KR
    Kim‐Kwang Raymond Choo

    The University of Texas at San Antonio, United States

    2 publications · 145 citations

    2

    h-index

  4. JZ
    Jinghui Zhong

    South China University of Technology, China

    1 publications · 71 citations

    1

    h-index

  5. NL
    Nengchao Lyu

    Wuhan University of Technology, China

    1 publications · 55 citations

    1

    h-index

1–5 of 261

Venues

  1. Expert Systems with Applications

    4 publications · 163 citations

    4

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  2. Applied Soft Computing

    5 publications · 121 citations

    4

    h-index

  3. IEEE Access

    3 publications · 186 citations

    3

    h-index

  4. 3

    h-index

  5. Procedia Computer Science

    2 publications · 35 citations

    2

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1–5