aalto1 untyped-item.component.html
P-MDP : A Framework to Optimize NFPs of Business Processes in Uncertain Environments
Loading...
Files
Access rights
openAccess
acceptedVersion
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Date
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
16
Series
Service-Oriented Computing - 23rd International Conference, ICSOC 2025, Proceedings, pp. 237-252, Lecture Notes in Computer Science ; Volume 16321
Abstract
In uncertain environments, compliance assurance for business processes faces the intertwined challenges posed by diverse non-functional properties (NFPs) and complex gateways in the models. While solutions like user-defined metrics and constraints empower businesses to act independently, or Markov Decision Process (MDP) enhance statistical algorithm design, they address uncertainties from different views and have not been considered together to tackle a holistic, integrated business and system uncertainties. This paper proposes Process-aware MDP (P-MDP), a framework that unifies the two divergent view to optimize NFPs for business processes operating under uncertainty. We devise a gateway-aware, lazy-evaluation reward mechanism supporting the key stakeholders – business managers – to customize metrics, algorithms, and constraints, and apply them on business processes. Experiments with the WSDREAM benchmark dataset show that P-MDP outperforms the state-of-the-art (SOTA) method constraint-satisfied service composition MDP (CSSC-MDP) at various scales. Moreover, P-MDP demonstrates superior generality and scalability, enabling stakeholders to generate better execution plans for business processes in complex scenarios.
Description
Other note
Citation
Peng, J, Zhu, J, Zhang, L & Truong, L 2026, P-MDP : A Framework to Optimize NFPs of Business Processes in Uncertain Environments. in M Aiello, I Georgievski, S Deng, J-M Murillo, B Benatallah & Z Wang (eds), Service-Oriented Computing - 23rd International Conference, ICSOC 2025, Proceedings. Lecture Notes in Computer Science, vol. 16321, Springer, pp. 237-252, International Conference on Service-Oriented Computing, Shenzhen, China, 01/12/2025. https://doi.org/10.1007/978-981-95-5015-9_18