RT Journal Article
T1 Business processes resource management using rewriting logic and deep-learning-based predictive monitoring
A1 Durán-Muñoz, Francisco Javier
A1 Pozas, Nicolás
A1 Rocha, Camilo
K1 Logística empresarial
K1 Planificación estratégica
AB A significant task in business process optimization is concerned with streamlining the allocation and sharing of resources. This paper presents an approach for analyzing business process provisioning under a resource prediction strategy based on deep learning. A timed and probabilistic rewrite theory specification formalizes the semantics of business processes. It is integrated with an external oracle in the form of a long short-term memory neural network that can be queried to predict how traces of the process may advance within a time frame. Comparison of execution time and resource occupancy under different parameters is included for several case studies, as well as details on the construction of the deep learning model and its integration with Maude.
PB Elsevier
YR 2024
FD 2024
LK https://hdl.handle.net/10630/35327
UL https://hdl.handle.net/10630/35327
LA eng
NO Francisco Durán, Nicolás Pozas, Camilo Rocha: Business processes resource management using rewriting logic and deep-learning-based predictive monitoring. J. Log. Algebraic Methods Program. 136: 100928 (2024)
NO The first two authors have been partially supported by projects TED2021-130666B-I00 and PID2021-125527NB-I00 funded by the Spanish government. The work of Rocha was partially funded by the Minciencias (Ministerio de Ciencia Tecnología e Innovación, Colombia) project PROMUEVA (BPIN 2021000100160).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026