Verifying soundness of business processes: A decision process Petri nets approach
This paper presents a trajectory-tracking approach for verifying soundness of workflow/Petri nets represented by a decision-process Petri net. Well-formed business processes correspond to sound workflow nets. The advantage of this approach is its ability to represent the dynamic behavior of the busi...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | México |
| Institución: | Instituto Politécnico Nacional |
| Repositorio: | Repositorio Digital del IPN |
| OAI Identifier: | oai:www.repositoriodigital.ipn.mx:123456789/19980 |
| Acceso en línea: | http://www.repositoriodigital.ipn.mx/handle/123456789/19980 |
| Access Level: | acceso abierto |
| Palabra clave: | Soundness Workflow nets Stability |
| Sumario: | This paper presents a trajectory-tracking approach for verifying soundness of workflow/Petri nets represented by a decision-process Petri net. Well-formed business processes correspond to sound workflow nets. The advantage of this approach is its ability to represent the dynamic behavior of the business process. We show that the problem of finding an optimum trajectory for validation of well-formed business processes is solvable. To prove our statement we use the Lyapunov stability theory to tackle the soundness verification problem for decision-process Petri nets. As a result, applying Lyapunov theory, the wellformed verification (soundness) property is solved showing that the workflow net representation using decision process Petri nets is uniformly practically stable. It is important to note that in a complexitytheoretic sense checking the soundness property is computationally tractable, we calculate the computational complexity for solving the problem. We show the connection between workflow nets and partially ordered decision-process Petri net used for business process representation and analysis. Our computational experiment of supply chains demonstrate the viability of the modeling and solution approaches for solving computer science problems. |
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