Business Processes Analysis with Resource-Aware Machine Learning Scheduling in Rewriting Logic

Francisco Durán, Daniela Martínez, Camilo Rocha

Producción: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

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 machine 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 a case study, as well as details on the building of the machine learning model and its integration with Maude.

Idioma originalInglés
Título de la publicación alojadaRewriting Logic and Its Applications - 14th International Workshop, WRLA 2022, Revised Selected Papers
EditoresKyungmin Bae
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas113-129
Número de páginas17
ISBN (versión impresa)9783031124402
DOI
EstadoPublicada - 2022
Evento14th International Workshop on Rewriting Logic and its Applications, WRLA 2022 - Munich, Alemania
Duración: 02 abr. 202203 abr. 2022

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen13252 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia14th International Workshop on Rewriting Logic and its Applications, WRLA 2022
País/TerritorioAlemania
CiudadMunich
Período02/04/2203/04/22

Huella

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