On reservation systems and queueing systems

McGinley, Mark; Zhu, Xiangfei; Veeraraghavan, Malathi

doi:10.1109/icist.2014.6920382

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…Accepting advance reservations can both guarantee customers' access to the service and help the operator better plan their operation (by knowing demand patterns in advance). McGinley et al (2014) compare the performance of queuing and reservation systems in telecommunication networks and determine the conditions under which reservation-mechanisms outperform queuing. Many transport networks also face a similar "reservation versus queuing" issue, with the relevant body of literature including studies of car rental (Oliveira et al 2016), parking (Latinopoulos et al 2017Lei and Ouyang 2017), and freeway usage (Wong 1997;Su et al 2013).…”

Section: Carsharing Vehicle Allocation Mechanismsmentioning

confidence: 99%

“…User-based relocation, which make use of users' spatial-temporal flexibility and engage them to relocate the vehicles, is also discussed in the literature (Jorge et al 2015;Xu et al 2018;Febbraro et al 2018). Another way of mitigating this imbalance is by introducing virtual queueing (VQ) and guaranteed advance reservation (GAR) mechanisms, which are common in fields with limited supply and volatile demand, such as communication network service, airlines, energy market and transport (McGinley et al 2014;Faria and Vale 2011;You 1999). These two mechanisms have potential benefits for both the operator and the user: for VQ, the operator puts customers onto a waiting list rather than rejecting them, and these users may receive bespoke pricing for this type of transaction; for GAR, the operator receives information regarding users' demand in advance and can act accordingly, and users potentially benefit from greater reliability.…”

Section: Introductionmentioning

confidence: 99%

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Traveller preferences for free-floating carsharing vehicle allocation mechanisms

Vine

Sivakumar

et al. 2019

Transportation Research Part C: Emerging Technologies

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Free-floating carsharing (FFCS) fleets are inherently volatile spatio-temporally, which presents both a logistical challenge for operators and a service reliability issue for customers. In this study we present a stated-choice survey to investigate the attractiveness to customers of two mechanisms for managing fleet volatility: Virtual Queuing (VQ) and Guaranteed Advance Reservations (GAR). We investigate socio-demographic features and "Big Five" personality traits that are associated ceteris paribus with choosing to use the existing FFCS service model, willingness-to-pay (WTP) for VQ and GAR, and risky-choice behaviour under the uncertainty of FFCS systems. Data (n=289; 232 employed in analysis) are sourced from existing users of a FFCS service in London, UK. Within the survey context, we found that customers are on average not willing to pay for VQ (i.e. negative WTP), however have £0.54 per journey WTP for GAR, with low-frequency FFCS users and users scoring highly on the Big Five "Conscientiousness" dimension having larger WTP for GAR. When analysing the two dimensions of uncertainty, we found that respondents exhibit riskseeking behaviour towards price and weaker and insignificant risk-aversion towards walking time. This pattern holds across the three standard model types of nonlinear risky choice behaviour that we investigated. The results are intended to be useful both to policymakers and carsharing operators who are likely, as the industry matures, to seek mechanisms to differentiate their service offers to better serve individual market segments with distinctive characteristics.

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Section: Carsharing Vehicle Allocation Mechanismsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Traveller preferences for free-floating carsharing vehicle allocation mechanisms

Vine

Sivakumar

et al. 2019

Transportation Research Part C: Emerging Technologies

View full text Add to dashboard Cite

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“…In order to solve the problem, this paper aims to proposed the accurate waiting time predictor and queue reservation system because the reservation can shift the customers from the peak period and the reserved customers is no need to wait for long time [17]. However, the research about the queue reservation has been lack, so this study also proposes the idea of queue reservation which can improve customer satisfaction and the system utilization.…”

Section: Introductionmentioning

confidence: 99%

Enhance System Utilization and Business Revenue with AI-based Queue Reservation System

Limlawan¹,

Anussornnitisarn²

2021

IJMLC

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Queue management is a crucial part of service industry. Business has to deal with the uncertainty of arrival customer and the trade-off between the costs of providing capacity and customer satisfaction. Matching service capacity with the arrival customer is difficult so the system utilization is low in the low periods and customers have to wait for a long time in the peak period. Due to long waiting, some customer abandons the queue before receiving service. Customer abandonment affects business revenue and the system utilization. To relieve the effect of the customer abandonment, this paper aims to propose Artificial Neural Network based waiting time predictor with queue reservation system. The proposed system increases the system utilization and increase customer satisfaction at the same time. Instead of abandonment, customers can reserve their place in queue if the waiting time is too long and they can do other activities while waiting. Moreover, the proposed system provides the accurate estimated waiting time to each customer instead of queue-length. The accurate waiting time enables arrival customers to better decide on the reservation options. 95% of our predicted waiting time is accurate within 5 minutes. Comparing to the system without the queue reservation system, the system utilization and the number of the arrival customer completed service improve 13% and 54% respectively

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“…The differences between reservation systems and queueing systems are character-ized, and categories of reservation systems and queueing systems are analyzed to understand the factors that influence why reservation systems and queueing systems may be used by different systems in the same category. This work has been submitted in a paper to Manufacturing and Service Operations Management [11].…”

Section: A General Reservation System Model (Grsm)mentioning

confidence: 99%

On Providing Fair Circuit/Virtual-Circuit Networking Services

McGinley¹

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It has become clear that widespread collaboration in the scientific community, which can increasingly be characterized by geographically distributed and large-scale projects, requires predictable network service [1]. Predictable network service needed by applications such as large file transfers, remote visualization, and remote instrumentation can only be offered on connection-oriented networks. Circuit-switched and virtual-circuit networks offer such connection-oriented services.This dissertation addresses four issues that inhibit wider adoption of connection-oriented service. From a theoretical perspective, we address reservation systems and queueing systems. An important consideration for a reservation system with multiple classes, as are necessary to provide a level of service matched with a specific use, is fairness. First, we present a novel three-step scheduling algorithm that finds the optimal solution to a multi-class, fairness-considering bin packing problem, and demonstrate how it can be used to ensure fairness in a reservation system. Second, with many types of reservation systems across different disciplines, we recognize a need for a uniform way to describe reservation systems, and so present a novel general reservation system model (GRSM), and analyze several examples of commonly encountered reservation and queueing systems to understand why certain systems belonging to the same category of examples use reservation systems while others use queueing systems.From an experimental perspective, we address performance and deployment issues with connection-oriented service. First, data-plane performance is paramount to being able to provide satisfactory connection-oriented service. To address this, we have performed an in-depth experimental study of the data-plane issues that arise in circuits, as well as comparing existing transport protocols to a novel implementation designed for circuits. Finally, to provide connection-oriented iv v service to end hosts, we present a solution that allows an off-the-shelf physical switch to be virtualized into multiple logical switches. Thus, connection-oriented service could be provided on the same existing substrate as connectionless service with no new infrastructure expenditures. AcknowledgmentsForemost, my sincerest thank you to Prof. Malathi Veeraraghavan, my advisor, who has unceasingly guided me in the completion of this work. It has been an incredibly valuable experience to benefit from her knowledge, experience, and generosity, and a pleasure to work with someone who brings an energy and intellectual curiosity to every discussion.

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On reservation systems and queueing systems

Cited by 4 publications

References 19 publications

Traveller preferences for free-floating carsharing vehicle allocation mechanisms

Traveller preferences for free-floating carsharing vehicle allocation mechanisms

Enhance System Utilization and Business Revenue with AI-based Queue Reservation System

On Providing Fair Circuit/Virtual-Circuit Networking Services

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