The overall objective of this paper is to introduce a customer oriented supplier selection
method. Although the supplier selection problem has previously been investigated, an …

We consider the problem of computing the satisfaction probability of a formula for stochastic
models with parametric uncertainty. We show that this satisfaction probability is a smooth …

The parameters of Markov chain models are often not known precisely. Instead of ignoring
this problem, a better way to cope with it is to incorporate the imprecision into the models …

This paper proposes and compares different techniques for maintenance optimization based
on Genetic Algorithms (GAs), when the parameters of the maintenance model are affected …

Many practical methods and different approaches have been proposed to assess Multi-State
Systems (MSS) reliability measures. The universal generating function (UGF) method …

We justify and discuss expressions for joint lower and upper expectations in imprecise
probability trees, in terms of the sub-and supermartingales that can be associated with such …

This study examines the dynamic stages of exploration and exploitation efforts by
organizations in their cybersecurity responses using multistate modeling. Using textual data …

We use the martingale-theoretic approach of game-theoretic probability to incorporate
imprecision into the study of randomness. In particular, we define several notions of …

Quantification of uncertainty is mostly done by the use of precise probabilities: for each event
A, a single (classical, precise) probability P (A) is used, typically satisfying Kolmogorov's …

Cost-effectiveness studies of medical innovations often suffer from data inadequacy. When
Markov chains are used as a modeling framework for such studies, this data inadequacy can …