Planning and Operations Research (Dagstuhl Seminar 18071)

Authors J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, Willem-Jan Van Hoeve and all authors of the abstracts in this report



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Author Details

J. Christopher Beck
Daniele Magazzeni
Gabriele Röger
Willem-Jan Van Hoeve
and all authors of the abstracts in this report

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J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, and Willem-Jan Van Hoeve. Planning and Operations Research (Dagstuhl Seminar 18071). In Dagstuhl Reports, Volume 8, Issue 2, pp. 26-63, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/DagRep.8.2.26

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 18071 "Planning and Operations Research". The seminar brought together researchers in the areas of Artificial Intelligence (AI) Planning, Constraint Programming, and Operations Research. All three areas have in common that they deal with complex systems where a huge space of interacting options makes it almost impossible to humans to take optimal or even good decisions. From a historical perspective, operations research stems from the application of mathematical methods to (mostly) industrial applications while planning and constraint programming emerged as subfields of artificial intelligence where the emphasis was traditionally more on symbolic and logical search techniques for the intelligent selection and sequencing of actions to achieve a set of goals. Therefore operations research often focuses on the allocation of scarce resources such as transportation capacity, machine availability, production materials, or money, while planning focuses on the right choice of actions from a large space of possibilities. While this difference results in problems in different complexity classes, it is often possible to cast the same problem as an OR, CP, or planning problem. In this seminar, we investigated the commonalities and the overlap between the different areas to learn from each other's expertise, bring the communities closer together, and transfer knowledge about solution techniques that can be applied in all areas.
Keywords
  • Artificial Intelligence
  • Automated Planning and Scheduling
  • Constraint Programming
  • Dynamic Programming
  • Heuristic Search
  • Mixed Integer Programming
  • Operations Research
  • Optimization
  • Real-world Applications
  • Reasoning under Uncertainty

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