Metaheuristic Batch Scheduling

Metaheuristic Batch Scheduling is a batch scheduling approach that belongs to the class of optimization methods relying on high-level, problem-independent search strategies, distinguished by its use of metaheuristic algorithms—such as genetic algorithms, simulated annealing, or particle swarm optimization—to efficiently explore large solution spaces and find near-optimal batch sequences in complex, constrained environments.

32

Publications

2K

Citations

73

Authors

38

Institutions

Publications per year

2017–2026

16

Authors

73

  1. MW
    Matthew Woolway

    University of the Witwatersrand, South Africa

    3 publications · 37 citations

    3

    h-index

  2. ZJ
    Zhaohong Jia

    Anhui University, China

    2 publications · 55 citations

    2

    h-index

  3. JY
    Joseph Y.‐T. Leung

    New Jersey Institute of Technology, United States

    2 publications · 45 citations

    2

    h-index

  4. TM
    Thokozani Majozi

    University of the Witwatersrand, South Africa

    2 publications · 25 citations

    2

    h-index

  5. SG
    Sergei Gorlatch

    University of Münster, Germany

    1 publications · 17 citations

    1

    h-index

1–5 of 73

Venues

  1. Computers & Industrial Engineering

    6 publications · 219 citations

    7

    h-index

  2. Computers & Operations Research

    3 publications · 150 citations

    3

    h-index

  3. Computers & Chemical Engineering

    2 publications · 816 citations

    2

    h-index

  4. Engineering Optimization

    2 publications · 118 citations

    2

    h-index

  5. International Journal of Production Research

    2 publications · 198 citations

    2

    h-index

1–5