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The paper is motivated by the stochastic comparison of the reliability
of non-repairable k-out-of-n systems.
The lifetime of such a system with nonidentical components is compared with the lifetime of a system with
identical components.
Formally the problem is as follows. Let Ui,i = 1,...,n, be positive
independent random variables with common distribution F.
For λi > 0 and µ > 0, let consider
Xi = Ui/λi and Yi = Ui/µ, i = 1,...,n.
Remark that this is no more than a change of scale for each...
For a given partial solution, the partial inverse problem is to modify the coefficients such that there is a full solution containing the partial solution, while the full solution becomes optimal under new coefficients, and the total modification is minimum. In this paper, we show that the partial inverse assignment problem and the partial inverse minimum cut problem are NP-hard if there are bound constraints on the changes of coefficients.
For a given partial solution,
the partial inverse problem is to modify the coefficients
such that there is a full solution containing the partial solution,
while the full solution becomes optimal under new coefficients, and
the total modification is minimum.
In this paper, we show that the partial inverse
assignment problem and the partial inverse minimum cut problem are NP-hard if
there are bound constraints on the changes of coefficients.
Single server queues with repeated attempts are useful in
the modeling of computer and telecommunication systems. In addition, we
consider in this paper the possibility of disasters. When a disaster
occurs, all the customers present in the system are destroyed
immediately. Using a regenerative approach, we derive a numerically
stable recursion scheme for the state probabilities. This model can be
employed to analyze the behaviour of a buffer in computers with virus
infections.
We consider a system consisting of two not necessarily identical exponential servers having a common Poisson arrival process. Upon arrival, customers inspect the first queue and join it if it is shorter than some threshold n. Otherwise, they join the second queue. This model was dealt with, among others, by Altman et al. [Stochastic Models20 (2004) 149–172]. We first derive an explicit expression for the Laplace-Stieltjes transform of the distribution underlying the arrival (renewal) process to...
We consider a system consisting of two not necessarily identical
exponential servers having a common Poisson arrival process. Upon
arrival, customers inspect the first queue and join it if it is
shorter than some threshold n. Otherwise, they join the second
queue. This model was dealt with, among others, by Altman et al. [Stochastic Models20 (2004) 149–172].
We first derive an explicit
expression for the Laplace-Stieltjes transform of the distribution
underlying the arrival (renewal) process to...
A vector is said to be an eigenvector of a square max-min matrix if . An eigenvector of is called the greatest -eigenvector of if and for each eigenvector . A max-min matrix is called strongly -robust if the orbit reaches the greatest -eigenvector with any starting vector of . We suggest an algorithm for computing the greatest -eigenvector of and study the strong -robustness. The necessary and sufficient conditions for strong -robustness are introduced and an efficient...
Ce travail porte sur l'optimisation des lignes
d'usinage pour la grande série. Une telle ligne comporte plusieurs
postes de travail, chacun étant équipé avec boîtiers multibroches. Un
boîtier multibroche exécute plusieurs opérations en parallèle.
Lors de la conception en avant-projet,
il est nécessaire d'affecter toutes les opérations à des boîtiers et
des postes de travail de sorte à minimiser le nombre de postes et de
boîtiers utilisés. Pour ce nouveau problème d'équilibrage des lignes
de production,...
This paper considers a distributed state estimation problem for multi-agent systems under state inequality constraints. We first give a distributed estimation algorithm by projecting the consensus estimate with help of the consensus-based Kalman filter (CKF) and projection on the surface of constraints. The consensus step performs not only on the state estimation but also on the error covariance obtained by each agent. Under collective observability and connective assumptions, we show that consensus...
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