Abstract
The application of workflow scheduling in managing individual actor’s personal worklist is one area that can bring great improvement to business process. However, current deterministic work cannot adapt to the dynamics and uncertainties in the management of personal worklist. For such an issue, this paper proposes a two-stage probabilistic approach which aims at assisting actors to flexibly manage their personal worklists. To be specific, the approach analyzes every activity instance’s continuous probability of satisfying deadline at the first stage. Based on this stochastic analysis result, at the second stage, an innovative scheduling strategy is proposed to minimize the overall deadline violation cost for an actor’s personal worklist. Simultaneously, the strategy recommends the actor a feasible worklist of activity instances which meet the required bottom line of successful execution. The effectiveness of our approach is evaluated in a real-world workflow management system and with large scale simulation experiments.
Supported by the NSFC (90718010), National Basic Research Program (973 Plan) under grant No. 2009CB320700, National High-Tech Development Program (863 Plan) under grant No. 2008AA042301 and 2007AA040607, and Program for New Century Excellent Talents in University.
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Han, R., Liu, Y., Wen, L., Wang, J. (2009). A Two-Stage Probabilistic Approach to Manage Personal Worklist in Workflow Management Systems. In: Meersman, R., Dillon, T., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2009. OTM 2009. Lecture Notes in Computer Science, vol 5870. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05148-7_5
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