Hinkelmann, KnutSprovieri, DanilloDiaz, DanielMazo, RaulEspaña, SergioRalyté, JolitaSouveyet, Carine2017-04-042017-04-04201610.1109/RCIS.2016.7549274http://hdl.handle.net/11654/24696https://doi.org/10.26041/fhnw-1019Organizations act in highly competitive markets, which forces them to be flexible. Constantly changing business requirements require flexible business processes. Case Management Model and Notation (CMMN) supports modeling run-time flexibility of partially structured business process models, but does not fully specify the control flow. Objective: The goal is to develop a planning algorithm that supports the case worker in planning case-based business processes at run-time. Method: We identify the requirements of run-time planning of partly structured processes by analyzing the admission process for the master degree at FHNW. To plan the process instance, we develop a planning algorithm. Our planning algorithm is evaluated using concrete cases provided by FHNW in order to demonstrate real application. Results: The planning algorithm reflects the requirements for serializing tasks at run-time. Conclusion: Our planning algorithm allows to automatically deriving context-specific execution plans for CMMN models at run-time.enArtificial IntelligenceBusiness ProcessCMMNPlanning04B - Beitrag Konferenzschrift57-64