the arc costs are assumed to be online parameters of the network and decisions should be made while the costs of arcs are not known. the policies determine the permitted nodes and arcs to traverse and they are generally defined according to the departure nodes of the current policy nodes. in on-line created tours arc costs are not available for decision makers. the on-line traversed nodes are f...

the probable lack of some arcs and nodes in the stochastic networks is considered in this paper, and its effect is shown as the arrival probability from a given source node to a given sink node. a discrete time markov chain with an absorbing state is established in a directed acyclic network. then, the probability of transition from the initial state to the absorbing state is computed. it is as...

A. A stochastic process is a collection of random variables {X t , t ∈ T }. B. A sample path or realization of a stochastic process is the collection of values assumed by the random variables in one realization of the random process, e.g. C. The state space is the collection of all possible values the random variables can take on, i.e. it is the sample space of the random variables. For example...

this paper presents a discrete-time single-server finite buffer n threshold policy queue with renewal input and discretemarkovian service process. the server terminates service whenever the system becomes empty, and recommencesservice as soon as the number of waiting customers in the queue is n. we obtain the system-length distributionsat pre-arrival and arbitrary epochs using the supplementary...

 In this paper we study the relative entropy rate between a homogeneous Markov chain and a hidden Markov chain defined by observing the output of a discrete stochastic channel whose input is the finite state space homogeneous stationary Markov chain. For this purpose, we obtain the relative entropy between two finite subsequences of above mentioned chains with the help of the definition of...

investors use different approaches to select optimal portfolio. so, optimal investment choices according to return can be interpreted in different models. the traditional approach to allocate portfolio selection called a mean - variance explains. another approach is markov chain. markov chain is a random process without memory. this means that the conditional probability distribution of the nex...

This paper presents a discrete-time single-server finite buffer N threshold policy queue with renewal input and discreteMarkovian service process. The server terminates service whenever the system becomes empty, and recommencesservice as soon as the number of waiting customers in the queue is N. We obtain the system-length distributionsat pre-arrival and arbitrary epochs using the supplementary...