Abstract
In situations of scarce resource availability, flexibility on which resources execute which tasks is key to process and system performance. Tightly coupled control flow and resource modeling hampers flexible resource allocation. Hence, in this work, we propose resource-driven process manipulation (RDPM) to enable the separation between the business and resource requirements for a process. RDPM enables process modelers to specify resource-specific requirements for the control flow as part of resource profiles, e.g., a machine (resource) requires configuration (task) before execution. Moreover, the resource is promoted to a first-class citizen in process-aware information systems and enabled to impact the execution. The basic concepts of RDPM are defined and an algorithm is provided to find valid resource allocations for a task. The approach is prototypically implemented and compared to existing modeling approaches w.r.t. complexity for the modeler and process participant.
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This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project number 277991500.
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Schumann, F., Rinderle-Ma, S. (2024). Resource-Driven Process Manipulation: Modeling Concepts and Valid Allocations. In: Sellami, M., Vidal, ME., van Dongen, B., Gaaloul, W., Panetto, H. (eds) Cooperative Information Systems. CoopIS 2023. Lecture Notes in Computer Science, vol 14353. Springer, Cham. https://doi.org/10.1007/978-3-031-46846-9_23
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