In this paper we review the literature on multi-component maintenance models with economic dependence. The emphasis is on papers that appeared after 1991, but there is an overlap with Section 2 of the most recent review paper by Cho and Parlar (1991). We distinguish between stationary models, where a long-term stable situation is assumed, and dynamic models, which can take information into account that becomes available only on the short term. Within the stationary models we choose a classification scheme that is primarily based on the various options of grouping maintenance activities: grouping either corrective or preventive maintenance, or combining preventive-maintenance actions with corrective actions. As such, this classification links up with the possibilities for grouped maintenance activities that exist in practice.

Applications of bulk queues to group testing models with incomplete identificationBar-Lev, S.K.; Parlar, M.; Perry, D.; Stadje, W.; van der Duyn Schouten, F.A. General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract A population of items is said to be ''group-testable'', (i) if the items can be classified as ''good'' and ''bad'', and (ii) if it is possible to carry out a simultaneous test on a batch of items with two possible outcomes: ''Success'' (indicating that all items in the batch are good) or ''failure'' (indicating a contaminated batch). In this paper, we assume that the items to be tested arrive at the group-testing centre according to a Poisson process and are served (i.e., group-tested) in batches by one server. The service time distribution is general but it depends on the batch size being tested. These assumptions give rise to the bulk queueing model M/G (m,M) /1, where m and M(>m) are the decision variables where each batch size can be between m and M. We develop the generating function for the steady-state probabilities of the embedded Markov chain. We then consider a more realistic finite state version of the problem where the testing centre has a finite capacity and present an expected profit objective function. We compute the optimal values of the decision variables (m, M) that maximize the expected profit. For a special case of the problem, we determine the optimal decision explicitly in terms of the Lambert function.

and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research-You may not further distribute the material or use it for any profit-making activity or commercial gain-You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim.

In this paper we deal with continuous time Markov decision drift processes (CTMDP), which permit both controls affecting jump rates of the process and impulsive controls causing immediate transitions. Between two successive jump epochs the state of the process evolves according to a deterministic drift function. Given a CTMDP we construct a sequence of discrete time Markov decision drift processes (DTMDP) with decreasing distance between the successive decision epochs. Sufficient conditions are provided under which the law of the CTMDP controlled by a fixed policy is the limit (in the sense of weak convergence of probability measures) of the laws of the approximating DTMDF's controlled by fixed discrete time policies. The conditions concern both the parameters of the CTMDP and the relation between the discrete time and continuous time policies. An application to a maintenance replacement model is given.

Analysis and computation of (n,N)van der Duyn Schouten, F.A.; Vanneste, S.G.