Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
Asymptotic behavior of the expansion method for open finite queueing networks
Computers and Operations Research
Manufacturing flow line systems: a review of models and analytical results
Queueing Systems: Theory and Applications - Special issue on queueing models of manufacturing systems
Queueing networks with blocking
Queueing networks with blocking
Open finite queueing networks with M/M/C/K parallel servers
Computers and Operations Research
Simulation with Arena
Optimum Discarding in a Bufferless System
Queueing Systems: Theory and Applications
Transform-free analysis of the GI/G/1/K queue through the decomposed Little's formula
Computers and Operations Research
Approximate analysis of M/G/c/c state-dependent queueing networks
Computers and Operations Research
Service and capacity allocation in M/G/c/c state-dependent queueing networks
Computers and Operations Research
A Two-Moment Approximation for the GI/G/c Queue with Finite Capacity
INFORMS Journal on Computing
Isolation Method in a Network of Queues
IEEE Transactions on Software Engineering
Buffer allocation in general single-server queueing networks
Computers and Operations Research
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
On the Evolutionary Optimization of Many Conflicting Objectives
IEEE Transactions on Evolutionary Computation
A simple algebraic approximation to the Erlang loss system
Operations Research Letters
Mathematics and Computers in Simulation
Queueing model analysis and scheduling strategy for embedded multi-core SoC based on task priority
Computers and Electrical Engineering
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Open zero-buffer multi-server general queueing networks occur throughout a number of physical systems in the semi-process and process industries. In this paper, we evaluate the performance of these systems in terms of throughput using the generalized expansion method (GEM) and compare our results with simulation. Secondly, we embed the performance evaluation in a multi-objective optimization setting. This multi-objective optimization approach results in the Pareto efficient curves showing the trade-off between the total number of servers used and the throughput. Experiments for a large number of settings and different network topologies are presented in detail.