This paper provides an overview of the historical evolution of reliability in the scientific area of operations research. Historical views and future perspectives are specifically offered with regards to reliability modeling and inference, treatment of uncertainty in reliability modelling and analysis, definition of importance measures for identifying those elements of a system which are critical for its reliability, optimization of the design, operation and maintenance of a system with respect to its reliability, adversarial issues, and the growing focus on machine learning for reliability modeling and optimization. The overview and perspectives given are rich but by no means they cover all the great developments and advancements done, nor they point at all still-open issues and coming challenges.

Fifty years of reliability in operations research

Zio E.
2024-01-01

Abstract

This paper provides an overview of the historical evolution of reliability in the scientific area of operations research. Historical views and future perspectives are specifically offered with regards to reliability modeling and inference, treatment of uncertainty in reliability modelling and analysis, definition of importance measures for identifying those elements of a system which are critical for its reliability, optimization of the design, operation and maintenance of a system with respect to its reliability, adversarial issues, and the growing focus on machine learning for reliability modeling and optimization. The overview and perspectives given are rich but by no means they cover all the great developments and advancements done, nor they point at all still-open issues and coming challenges.
2024
Adversarial decision making
Aleatory uncertainty
Bayesian theory
Epistemic uncertainty
Game theory
Importance measures
Machine learning
Operations research
Optimization
Reliability
Statistical inference
Stochastic process
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1278052
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