Modeling and analysis of stochastic systems
Modeling and analysis of stochastic systems
Stochastic dynamic programming and the control of queueing systems
Stochastic dynamic programming and the control of queueing systems
A Tandem Queue with a Movable Server: An Eigenvalue Approach
SIAM Journal on Matrix Analysis and Applications
A two-stage tandem queue attended by a moving server with holding and switching costs
Queueing Systems: Theory and Applications
Control of a Single-Server Tandem Queueing System with Setups
Operations Research
Dynamic Server Allocation for Queueing Networks with Flexible Servers
Operations Research
EXPECTED MAKESPAN MINIMIZATION ON IDENTICAL MACHINES IN TWO INTERCONNECTED QUEUES
Probability in the Engineering and Informational Sciences
Queueing Systems: Theory and Applications
On the Introduction of an Agile, Temporary Workforce into a Tandem Queueing System
Queueing Systems: Theory and Applications
Optimal control of flexible servers in two tandem queues with operating costs
Probability in the Engineering and Informational Sciences
Priority tandem queueing model with admission control
Computers and Industrial Engineering
Queueing Systems: Theory and Applications
Dynamic server allocation for unstable queueing networks with flexible servers
Queueing Systems: Theory and Applications
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We consider the optimal control of two parallel servers in a two-stage tandem queuing system with two flexible servers. New jobs arrive at station 1, after which a series of two operations must be performed before they leave the system. Holding costs are incurred at rate h1 per unit time for each job at station 1 and at rate h2 per unit time for each job at station 2.The system is considered under two scenarios; the collaborative case and the noncollaborative case. In the prior, the servers can collaborate to work on the same job, whereas in the latter, each server can work on a unique job although they can work on separate jobs at the same station. We provide simple conditions under which it is optimal to allocate both servers to station 1 or 2 in the collaborative case. In the noncollaborative case, we show that the same condition as in the collaborative case guarantees the existence of an optimal policy that is exhaustive at station 1. However, the condition for exhaustive service at station 2 to be optimal does not carry over. This case is examined via a numerical study.