Workflow management: models, methods, and systems
Workflow management: models, methods, and systems
Duration Histograms for Workflow Systems
Proceedings of the IFIP TC8 / WG8.1 Working Conference on Engineering Information Systems in the Internet Context
Applying scheduling techniques to minimize the number of late jobs in workflow systems
Proceedings of the 2004 ACM symposium on Applied computing
An architecture for workflow scheduling under resource allocation constraints
Information Systems
Task Scheduling for a TemporalWorkflow Management System
TIME '06 Proceedings of the Thirteenth International Symposium on Temporal Representation and Reasoning
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Deadline-based escalation in process-aware information systems
Decision Support Systems
Scheduling Algorithms
Breadth-first heuristic search
Artificial Intelligence
Personal schedules for workflow systems
BPM'03 Proceedings of the 2003 international conference on Business process management
A probabilistic approach to reduce the number of deadline violations and the tardiness of workflows
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part I
Modeling the behavior of dispatching rules in workflow systems: a statistical approach
CRIWG'05 Proceedings of the 11th international conference on Groupware: design, Implementation, and Use
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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.