Abstract
This paper introduces a novel strategic optimization methodology for Uninorm Petri Nets tailored for intelligent information and decision support systems operating under uncertainty. The proposed hybrid framework, termed Optimized Uninorm Petri Nets, bridges the gap between theoretical modeling and practical system development by integrating algebraic optimization with simulation-based verification. The methodology is built on two strategic pillars crucial for modern information systems engineering. The first pillar, strategic logic optimization, utilizes a mathematically constrained selection of uninorm operator triplets (In, Trs, Out) to ensure the structural reliability, precision, and efficiency of the system's core decision-making logic. The second pillar focuses on dynamic system alignment through a simulation-driven analysis of the uninorm neutral element e in (0, 1), which optimizes system dynamics and directly embeds a "transparent-by-design" philosophy aligning with Explainable AI standards. Finally, the methodology's utility for information systems development is validated through a practical implementation in a real-world technical control system. Comparative analyses demonstrate that Optimized Uninorm Petri Nets offer superior adaptability, precision in modeling transitional states, and architectural robustness compared to traditional fuzzy frameworks, proving to be a highly effective tool for engineering next-generation intelligent information systems.
Paper Type
Short Paper
DOI
10.62036/ISD.2026.38
A Novel Methodology for the Strategic Optimization of Uninorm Petri Nets in Intelligent Information Systems
This paper introduces a novel strategic optimization methodology for Uninorm Petri Nets tailored for intelligent information and decision support systems operating under uncertainty. The proposed hybrid framework, termed Optimized Uninorm Petri Nets, bridges the gap between theoretical modeling and practical system development by integrating algebraic optimization with simulation-based verification. The methodology is built on two strategic pillars crucial for modern information systems engineering. The first pillar, strategic logic optimization, utilizes a mathematically constrained selection of uninorm operator triplets (In, Trs, Out) to ensure the structural reliability, precision, and efficiency of the system's core decision-making logic. The second pillar focuses on dynamic system alignment through a simulation-driven analysis of the uninorm neutral element e in (0, 1), which optimizes system dynamics and directly embeds a "transparent-by-design" philosophy aligning with Explainable AI standards. Finally, the methodology's utility for information systems development is validated through a practical implementation in a real-world technical control system. Comparative analyses demonstrate that Optimized Uninorm Petri Nets offer superior adaptability, precision in modeling transitional states, and architectural robustness compared to traditional fuzzy frameworks, proving to be a highly effective tool for engineering next-generation intelligent information systems.
Recommended Citation
Suraj, Z. & Grochowalski, P.(2026). A Novel Methodology for the Strategic Optimization of Uninorm Petri Nets in Intelligent Information Systems. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.38