Research

Timefold provides a strong platform for metaheuristics research. Its extensive array of pre-existing use cases simplifies the process of objectively comparing your new algorithms with current ones, aiding in thorough and efficient exploration in this field.

To reference Timefold or the user manual, please use this BibTeX reference:

@manual{timefold,
  author        = {De Smet, Geoffrey and Petrovický, Lukáš and open source contributors},
  title         = {Timefold documentation},
  year          = {2023},
  organization  = {Timefold BV or third-party contributors},
  url           = {https://timefold.ai},
  note          = {Timefold is an open source AI solver for Java, Python or Kotlin}
}

Timefold related papers

Multithreaded incremental solving for local search based metaheuristics with step chasing by Geoffrey De Smet, Tony Wauters (2020)

Paper: PDF

Publication: Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling - PATAT 2021: Volume I

ISBN: 978-0-9929984-3-1
Layout planning in assembly line kitting - a constraint programming approach by Christoffer Fink et al. (2021)

Paper: Link

Publication: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

ISBN: 978-1-7281-2989-1
Extending the OptaPlanner scheduling engine with the implementation of the Ruin and Recreate principle (Polish) by Michał Dudkiewicz (2023)

Paper: Link

If your paper relates to Timefold, let us know and we’ll add it here.