Optimal admission and routing with congestion-sensitive customer classes

Aslan, Ayse

Abstract

This paper considers optimal admission and routing control in multi-class service systems in which customers can either receive quality regular service which is subject to congestion or can receive congestion-free but less desirable service at an alternative service station, which we call the self-service station. We formulate the problem within the Markov decision process framework and focus on characterizing the structure of dynamic optimal policies which maximize the expected long-run rewards. For this, value function and sample path arguments are used. The congestion sensitivity of customers is modeled with class-independent holding costs at the regular service station. The results show how the admission rewards of customer classes affect their priorities at the regular and self-service stations. We explore that the priority for regular service may not only depend on regular service admission rewards of classes but also on the difference between regular and self-service admission rewards. We show that optimal policies have monotonicity properties, regarding the optimal decisions of individual customer classes such that they divide the state space into three connected regions per class.

Citation

Aslan, A. (2022). Optimal admission and routing with congestion-sensitive customer classes. Probability in the Engineering and Informational Sciences, 36(3), 774-798. https://doi.org/10.1017/s0269964821000073

• Journal Article Type: Article
• Acceptance Date: Feb 1, 2021
• Online Publication Date: Mar 1, 2021
• Publication Date: 2022-07
• Deposit Date: Mar 21, 2022
• Publicly Available Date: Mar 21, 2022
• Journal: Probability in the Engineering and Informational Sciences
• Print ISSN: 0269-9648
• Electronic ISSN: 1469-8951
• Publisher: Cambridge University Press
• Peer Reviewed: Peer Reviewed
• Volume: 36
• Issue: 3
• Pages: 774-798
• DOI: https://doi.org/10.1017/s0269964821000073
• Keywords: admission control, congestion, Markov decision processes, revenue management, routing control
• Public URL: http://researchrepository.napier.ac.uk/Output/2855714