Admission Control of Quasi-Reversible Queueing Systems: Optimization and Reinforcement Learning

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Comte, Céline, Moyal, Pascal
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866914396798713856
author Comte, Céline
Moyal, Pascal
author_facet Comte, Céline
Moyal, Pascal
contents In this paper, we introduce a versatile scheme for optimizing the arrival rates of quasi-reversible queueing systems. We first propose an alternative definition of quasi-reversibility that encompasses reversibility and highlights the importance of the definition of customer classes. Then we introduce balanced arrival control policies, which generalize the notion of balanced arrival rates introduced in the context of Whittle networks, to the much broader class of quasi-reversible queueing systems. We prove that supplementing a quasi-reversible queueing system with a balanced arrival-control policy preserves the quasi-reversibility, and we specify the form of the stationary measures. We revisit two canonical examples of quasi-reversible queueing systems, Whittle networks and order-independent queues. Lastly, we focus on the problem of admission control and leverage our results in the frameworks of optimization and reinforcement learning.
format Preprint
id arxiv_https___arxiv_org_abs_2505_16353
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Admission Control of Quasi-Reversible Queueing Systems: Optimization and Reinforcement Learning
Comte, Céline
Moyal, Pascal
Machine Learning
Optimization and Control
Probability
In this paper, we introduce a versatile scheme for optimizing the arrival rates of quasi-reversible queueing systems. We first propose an alternative definition of quasi-reversibility that encompasses reversibility and highlights the importance of the definition of customer classes. Then we introduce balanced arrival control policies, which generalize the notion of balanced arrival rates introduced in the context of Whittle networks, to the much broader class of quasi-reversible queueing systems. We prove that supplementing a quasi-reversible queueing system with a balanced arrival-control policy preserves the quasi-reversibility, and we specify the form of the stationary measures. We revisit two canonical examples of quasi-reversible queueing systems, Whittle networks and order-independent queues. Lastly, we focus on the problem of admission control and leverage our results in the frameworks of optimization and reinforcement learning.
title Admission Control of Quasi-Reversible Queueing Systems: Optimization and Reinforcement Learning
topic Machine Learning
Optimization and Control
Probability
url https://arxiv.org/abs/2505.16353