Scheduling Analytics

Scheduling Analytics is a subfield of operations analytics that applies data-driven quantitative modeling—encompassing descriptive, predictive, and prescriptive methods—to design, evaluate, and optimize the allocation and timing of tasks and resources in scheduling systems under operational constraints and uncertainty.

177

Publications

6.7K

Citations

534

Authors

242

Institutions

Publications per year

2017–2026

81

Authors

534

  1. CB
    Cynthia Barnhart

    Massachusetts Institute of Technology, United States

    4 publications · 562 citations

    4

    h-index

  2. MV
    Mario Vanhoucke

    Ghent University, Belgium

    4 publications · 102 citations

    4

    h-index

  3. SS
    Sharan Srinivas

    University of Missouri, United States

    3 publications · 235 citations

    3

    h-index

  4. CJ
    Chang‐Hyeon Joh

    Eindhoven University of Technology, Netherlands

    3 publications · 79 citations

    3

    h-index

  5. JP
    John Polak

    Imperial College London, United Kingdom

    2 publications · 42 citations

    2

    h-index

1–5 of 534

Venues

  1. European Journal of Operational Research

    9 publications · 387 citations

    9

    h-index

  2. Computers & Operations Research

    6 publications · 168 citations

    6

    h-index

  3. INFORMS Journal on Applied Analytics

    5 publications · 221 citations

    5

    h-index

  4. Omega

    5 publications · 127 citations

    5

    h-index

  5. Journal of Manufacturing Systems

    4 publications · 256 citations

    4

    h-index

1–5