Abstract
In this paper we consider the dynamic allocation of customers to queues and study the performance of neural networks applied to the problem. The queueing system consists of N parallel distinct servers, each of which has its own queue with infinite capacity. A controller allocates each arriving customer to one of the servers at arrival epoch, who maximizes the probability of starting service for the customer in the earliest time. A neural network is incorporated into the controller, so that the neural controller can make an allocation decision adaptively to changing situations. We present a simple training method for the neural controller. We consider two types of neural networks (BP and LVQ3) and compare their performance in numerical examples.
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© 1993 Springer-Verlag/Wien
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Takinami, J., Matsumoto, Y., Okino, N. (1993). Performance Evaluation of Neural Networks Applied to Queueing Allocation Problem. In: Albrecht, R.F., Reeves, C.R., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7533-0_47
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DOI: https://doi.org/10.1007/978-3-7091-7533-0_47
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82459-7
Online ISBN: 978-3-7091-7533-0
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