Modeling uncertainty using partial information
Information Sciences: an International Journal
Possibility Theory, Probability Theory and Multiple-Valued Logics: A Clarification
Annals of Mathematics and Artificial Intelligence
Evolutionary Multi-objective Ranking with Uncertainty and Noise
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Flowgraph Models for Multistate Timeto-Event Data (Wiley Series in Probability and Statistics)
Flowgraph Models for Multistate Timeto-Event Data (Wiley Series in Probability and Statistics)
Representing parametric probabilistic models tainted with imprecision
Fuzzy Sets and Systems
Imprecise markov chains and their limit behavior
Probability in the Engineering and Informational Sciences
Discrete time Markov chains with interval probabilities
International Journal of Approximate Reasoning
Possibility theory and statistical reasoning
Computational Statistics & Data Analysis
Reliability-based optimization using evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Maximal confidence intervals of the interval-valued belief structure and applications
Information Sciences: an International Journal
On the fusion of imprecise uncertainty measures using belief structures
Information Sciences: an International Journal
Multi-objective optimization of problems with epistemic uncertainty
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Representing partial ignorance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Joint Propagation and Exploitation of Probabilistic and Possibilistic Information in Risk Assessment
IEEE Transactions on Fuzzy Systems
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The aim of this work is to assess the performance of a maintenance policy when a stochastic model of the life of the component of interest is known, but relies on parameters that are imprecisely known, and only through information elicited from experts. The case in which the information used to feed the model comes from a single expert has been investigated by the authors in a previous work. This paper deals with the different situation in which a number of experts are involved in the elicitation of the uncertain parameters; in particular, each expert provides an interval he/she believes containing the unknown value of the parameter which he/she is knowledgeable about. The different type of available information calls for the development of a different method to represent and propagate the associated uncertainty. Resorting to Probability theory to address this issue is questionable. Then, a technique based on the Dempster-Shafer Theory of Evidence (DSTE) is embraced in this work, which allows facing a practical case study concerning the check valve of a turbo-pump lubricating system in a Nuclear Power Plant. The output of such method consists of couples of Lower and Upper cumulative distributions describing the uncertainty in the maintenance performance indicators of interest (i.e., unavailability and costs), which accounts for both the aleatory and epistemic contributions.