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EnglishReplacement planning is critical to guarantee continuity of operations in business processes in case of personnel unavailability. In this work, we propose a data-driven approach for supporting resource replacement that makes use of logs of past process executions to model a social network of resources. On this top, a similarity measure among resources is exploited to assign tasks of unavailable resource to the available ones through an Integer Linear Model.
| Titolo: | How to Cope with Personnel Unavailability? Process Mining May Help! |
| Autori: | |
| Data di pubblicazione: | 2020 |
| Serie: | |
| Abstract: | Replacement planning is critical to guarantee continuity of operations in business processes in case of personnel unavailability. In this work, we propose a data-driven approach for supporting resource replacement that makes use of logs of past process executions to model a social network of resources. On this top, a similarity measure among resources is exploited to assign tasks of unavailable resource to the available ones through an Integer Linear Model. |
| Handle: | http://hdl.handle.net/11566/283920 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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