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.
How to Cope with Personnel Unavailability? Process Mining May Help! / Chiorrini, A.; Diamantini, C.; Potena, D.; Storti, E.. - 2646:(2020), pp. 234-241. (Intervento presentato al convegno 28th Italian Symposium on Advanced Database Systems, SEBD 2020 nel 2020).
How to Cope with Personnel Unavailability? Process Mining May Help!
Chiorrini A.;Diamantini C.;Potena D.;Storti E.
2020-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
