Analysis of polling systems
On the optimal control of two queues with server setup times and its analysis
SIAM Journal on Computing
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Queueing Systems: Theory and Applications - Polling models
Optimization of Polling Systems
Performance '90 Proceedings of the 14th IFIP WG 7.3 International Symposium on Computer Performance Modelling, Measurement and Evaluation
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
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This paper deals with the problem of scheduling a server in a polling system with multiple queues and complete information. We represent the polling policy by a neural network; namely, given the number of waiting customers in each queue, the server determines next queue he should visit according to the output of the neural network. By using the simulated annealing method, we improve the neural polling policy in such a way that the mean delay of customers is minimized. Numerical results show that the present approach is especially valid for asymmetric polling systems whose analytical optimization is considered intractable.