Genetic Algorithm Smoothing

Genetic Algorithm Smoothing is a resource smoothing method that employs genetic algorithms to optimize the allocation and scheduling of project resources by iteratively evolving feasible solutions through selection, crossover, and mutation operators.

39

Publications

1.7K

Citations

117

Authors

63

Institutions

Publications per year

2017–2026

13

Authors

117

  1. LA
    Lee Altenberg

    University of Hawaiʻi at Mānoa, United States

    2 publications · 106 citations

    2

    h-index

  2. XC
    Xinye Cai

    Nanjing University of Aeronautics and Astronautics, China

    1 publications · 14 citations

    1

    h-index

  3. HT
    Hidetoshi Takeshita

    Keio University, Japan

    1 publications · 19 citations

    1

    h-index

  4. YG
    Yongkang Gong

    Xi'an Institute of Optics and Precision Mechanics, China

    1 publications · 12 citations

    1

    h-index

  5. DO
    Driss Ouazar

    Ecole Mohammadia d'Ingénieurs, Morocco

    1 publications · 20 citations

    1

    h-index

1–5 of 117

Venues

  1. Computers and Electronics in Agriculture

    1 publications · 15 citations

    1

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  2. SSRN Electronic Journal

    Repository · 1 publications · 67 citations

    1

    h-index

  3. Materials Today Proceedings

    1 publications · 14 citations

    1

    h-index

  4. Construction Management and Economics

    1 publications · 22 citations

    1

    h-index

  5. IEEE Transactions on Neural Networks

    1 publications · 287 citations

    1

    h-index

1–5