Modeling and Analysis of Workflows Using Petri Nets
Journal of Intelligent Information Systems - Special issue on workflow management systems
On the automatic generation of workflow processes based on product structures
Computers in Industry
Distributed and Parallel Databases
Lectures on Petri Nets I: Basic Models, Advances in Petri Nets, the volumes are based on the Advanced Course on Petri Nets
An Introduction to the Theoretical Aspects of Coloured Petri Nets
A Decade of Concurrency, Reflections and Perspectives, REX School/Symposium
Business Process Execution Language for Web Services BPEL and BPEL4WS 2nd Edition
Business Process Execution Language for Web Services BPEL and BPEL4WS 2nd Edition
Workflows and e-Science: An overview of workflow system features and capabilities
Future Generation Computer Systems
STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Modern Business Process Automation: YAWL and its Support Environment
Modern Business Process Automation: YAWL and its Support Environment
Business process management: a survey
BPM'03 Proceedings of the 2003 international conference on Business process management
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Workflow resource pattern modelling and visualization
ACSC '13 Proceedings of the Thirty-Sixth Australasian Computer Science Conference - Volume 135
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Many modern business environments employ software to automate the delivery of workflows; whereas, workflow design and generation remains a laborious technical task for domain specialists. Several different approaches have been proposed for deriving workflow models. Some approaches rely on process data mining approaches, whereas others have proposed derivations of workflow models from operational structures, domain specific knowledge or workflow model compositions from knowledge-bases. Many approaches draw on principles from automatic planning, but conceptual in context and lack mathematical justification. In this paper we present a mathematical framework for deducing tasks in workflow models from plans in mechanistic or strongly controlled work environments, with a focus around automatic plan generations. In addition, we prove an associative composition operator that permits crisp hierarchical task compositions for workflow models through a set of mathematical deduction rules. The result is a logical framework that can be used to prove tasks in workflow hierarchies from operational information about work processes and machine configurations in controlled or mechanistic work environments.