Improving the performance of time-constrained workflow processing
Journal of Systems and Software
On Structured Workflow Modelling
CAiSE '00 Proceedings of the 12th International Conference on Advanced Information Systems Engineering
Extracting the workflow critical path from the extended well-formed workflow schema
Journal of Computer and System Sciences
International Journal of Intelligent Systems
Development of process execution rules for workload balancing on agents
Data & Knowledge Engineering - Special issue: Business process management
Translating unstructured workflow processes to readable BPEL: Theory and implementation
Information and Software Technology
Time Distribution in Structural Workflow Nets
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Using Templates to Predict Execution Time of Scientific Workflow Applications in the Grid
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Dwelling time probability density distribution of instances in a workflow model
Computers and Industrial Engineering
Process modeling for simulation
Computers in Industry
Time prediction based on process mining
Information Systems
Tabu search heuristics for workflow resource allocation simulation optimization
Concurrency and Computation: Practice & Experience
An approximate analysis of expected cycle time in business process execution
BPM'06 Proceedings of the 2006 international conference on Business Process Management Workshops
An analysis and taxonomy of unstructured workflows
BPM'05 Proceedings of the 3rd international conference on Business Process Management
Performance modeling and analysis of workflow
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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To analyze and optimize time performance of business process for faster response to customer demands, this study aims to develop a novel method for estimating the cycle time of business processes (or workflows) with many-to-many relationships between resources and activities based on individual worklists. The developed method for estimating business process cycle time is based on M/Hn/1/~ queuing model and the joint distribution theory of random variables. The feasibility and effectiveness of the proposed method are verified by comparison with the existing methods with case studies. The results have shown that the proposed method can provide a more accurate estimation than conventional approaches.