Probabilistic Scheduling

Probabilistic Scheduling is a task scheduling approach that belongs to the class of scheduling methods in which uncertainty in task execution times, resource availability, or environmental conditions is explicitly modeled using probability distributions, distinguishing it from deterministic scheduling by incorporating stochastic models to compute the likelihood of meeting temporal constraints.

378

Publications

23.7K

Citations

861

Authors

423

Institutions

Publications per year

2017–2026

87

Authors

861

  1. KD
    K. D. Glazebrook

    Newcastle University, United Kingdom

    17 publications · 515 citations

    12

    h-index

  2. XC
    Xiaoqiang Cai

    Chinese University of Hong Kong, Hong Kong SAR China

    8 publications · 259 citations

    8

    h-index

  3. LC
    Liliana Cucu‐Grosjean

    Institut national de recherche en sciences et technologies du numérique, France

    6 publications · 113 citations

    6

    h-index

  4. XZ
    Xian Zhou

    Hong Kong Polytechnic University, Hong Kong SAR China

    6 publications · 176 citations

    6

    h-index

  5. LS
    Luca Santinelli

    Office National d'Études et de Recherches Aérospatiales, France

    5 publications · 75 citations

    5

    h-index

1–5 of 861

Venues

  1. Management Science

    11 publications · 1.2K citations

    11

    h-index

  2. Operations Research

    11 publications · 737 citations

    11

    h-index

  3. 8

    h-index

  4. Computers & Industrial Engineering

    7 publications · 204 citations

    7

    h-index

  5. Naval Research Logistics (NRL)

    6 publications · 177 citations

    6

    h-index

1–5