Proceedings of the
35th European Safety and Reliability Conference (ESREL2025) and
the 33rd Society for Risk Analysis Europe Conference (SRA-E 2025)
15 – 19 June 2025, Stavanger, Norway
Uncertainty Quantification and Design Optimization Using Multi-Objective Optimization Techniques
1Industrial and Systems Engineering Graduate Program (PPGEPS), Pontifical Catholic University of Paraná (PUCPR). Brazil.
2Faculty of Engineering, Shinshu University. Japan.
ABSTRACT
The NASA-DNV challenge problem aims to develop methodologies for Uncertainty Quantification (UQ) in safety-critical and high-consequence systems with sparse or expensive data. The challenge is designed to be discipline-independent while capturing the complexities of real-world engineered systems. It consists of two key problems: (1) quantifying both aleatory and epistemic uncertainties by integrating computational models with real system data, and (2) optimizing control variables to balance performance and risk. Given the presence of conflicting objectives in both problems, multi-objective optimization techniques provide a promising approach for simultaneously addressing these trade-offs. This paper explores the role of multi-objective optimization in UQ and control optimization within the challenge framework.
Keywords: Multiobjective optimization, Uncertainty quantification, DNV challenge.
