This investigation deals with multi server queue with balking. The customers arrive in poisson fashion and independent of time, under the assumption that system is initially empty. The number of customers in the system is stochastically increasing and distributed in steady state (stationary state) as required. The expressions for the measure of the speed of convergence from transient state to s...

In the present study, we analyze the multi-channel service system with ordered entryfrom finite-source and finite-storage at each channel. The arrival and service rates are assumedto be state dependent. The steady state probabilities of the system are obtained by usingChapmann-Kolmogorov equations. Some other performance indices viz. utilization of servers,expected number of units in the system...

multi agent markov decision processes (mmdps), as the generalization of markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for multi agent reinforcement learning. in this paper, a generalized learning automata based algorithm for finding optimal policies in mmdp is proposed. in the proposed algorithm, mmdp ...

A CSS1†is a system with the continues-state components. When a component has the ability to obtain all the situations from completely working to completely failed, it named continues-state component. In the real world, performance rate of elements are continuous and decrease by time. Continuity of components causes infinite working states and grows up the system states. In this paper we propose...

in this paper, we study different methods of solving joint redundancy-availability optimization for series-parallel systems with multi-state components. we analyzed various effective factors on system availability in order to determine the optimum number and version of components in each sub-system and consider the effects of improving failure rates of each component in each sub-system and impr...

Multi agent Markov decision processes (MMDPs), as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for Multi agent Reinforcement Learning. In this paper, a generalized learning automata based algorithm for finding optimal policies in MMDP is proposed. In the proposed algorithm, MMDP ...

This paper has been worked on a RAP with multi-state components and the performance rate of each component working state may increase by spending technical and organizational activities costs. Whereas RAP belongs to Np-Hard problems, we used Genetic algorithm (GA) and simulated annealing (SA) and for solving the presented problem and calculating system reliability universal generating function ...

this paper examines critically the contributions of cournot, jevons and walras as the founders of classical mathematical economics from a methodological standpoint. advances in different economic schools and doctrines in the 19th century produced an environment of multi-dimensionality in economic analysis which was regarded by the pioneers of classical mathematical economists as a chaotic state...