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Planning and Operations Research (Dagstuhl Seminar 18071) Beck, J. Christopher Magazzeni, Daniele Röger, Gabriele Van Hoeve, Willem-Jan Artificial Intelligence Automated Planning and Scheduling Constraint Programming Dynamic Programming Heuristic Search Mixed Integer Programming Operations Research Optimization Real-world Applications Reasoning under Uncertainty 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik J. Christopher Beck and Daniele Magazzeni and Gabriele Röger and Willem-Jan Van Hoeve 2018 Is Part Of Dagstuhl Reports, Volume 8, Issue 2 (2018) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.8.2.26 urn:nbn:de:0030-drops-92894 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.2.26 eng https://creativecommons.org/licenses/by/3.0/legalcode