Analysis and Comparison of Queues with Different Levels of Delay Information.

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Date

2007

Authors

Guo, Pengfei

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Zipkin, Paul H.
Kulkarni, Vidyadhar G.
Majumder, Pranab
Song, Jing-Sheng (Jeannette)

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Abstract

Information about delays can enhance service quality in many industries. Delay information can take many forms, with different degrees of precision. Different levels of information have different effects on customers and so on the overall system. The goal of this research is to explore these effects. We first consider a queue with balking under three levels of delay information: No information, partial information (the system occupancy) and full information (the exact waiting time). We assume Poisson arrivals, independent, exponential service times, and a single server. Customers decide whether to stay or balk based on their expected waiting costs, conditional on the information provided. By comparing the three systems, we identify some important cases where more accurate delay information improves performance. In other cases, however, information can actually hurt the provider or the customers. We then investigate the impacts on the system of different cost functions and weight distributions. Specifically, we compare systems where these parameters are related by various stochastic orders, under different information scenarios. We also explore the relationship between customer characteristics and the value of information. The results here are mostly negative. We find that the value of information need not be greater for less patient or more risk-averse customers. After that, we extend our analysis to systems with phase-type service times. Our analytical and numerical results indicate that the previous conclusions about systems with exponential service times still hold for phase-type service times. We also show that service-time variability degrades the system’s performance. At last, we consider two richer models of information: In the first model, an arriving customer learns an interval in which the system occupancy falls. In the second model, each customer’s service time is the sum of a geometric number of i.i.d. exponential phases, and an arriving customer learns the total number of phases remaining in the system. For each information model, we compare two systems, identical except that one has more precise information. We study the effects of information on performance as seen by the service provider and the customers.

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Guo, Pengfei (2007). Analysis and Comparison of Queues with Different Levels of Delay Information. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/189.

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