Mobility Compass

Discover mobility and transportation research. Find experts, partners, networks.

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The Mobility Compass is an open tool for improving networking and interdisciplinary exchange within mobility and transport research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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PeopleLocationsStatistics
Ziakopoulos, ApostolosAthens
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Vigliani, AlessandroTurin
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Catani, JacopoRome
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Statheros, ThomasStevenage
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Guglieri, GiorgioTurin
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Liu, Meiqi
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Turunen, Anu W.
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Antunes, Carlos Henggeler
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Krasnov, Oleg A.
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Bruneel, Herwig

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in Cooperation with on an Cooperation-Score of 37%

Topics

  • vehicle
  • customer
  • queuing
  • highway traffic
  • intersection
  • motivation
  • turning lane
  • road
  • variable
  • production
  • employee
  • communication system
  • public transport
  • theory
  • comfort
  • estimating
  • density
  • submarine
  • traffic density
  • travel
  • engineering
  • neighborhood
  • traffic flow
  • transient
  • travel time
  • local traffic
  • flux
  • traffic model
  • fluid
  • commuter
  • game theory
  • waiting time
  • Statistic
  • infrastructure
  • chain
  • contrast
  • Markov chain
  • airport
  • security
  • automobile
  • estimate
  • filter
  • T intersection
  • show 13 more
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Publications

  • 2022Performance analysis of a continuous-time two-class global first-come-first-served queue with two servers and presorting1citations
  • 2016Discrete-time queues with variable service capacity: a basic model and its analysis10citations
  • 2015Public vs. personal transportation: a rational choice based on queueing theorycitations
  • 2014Rush hour roulette and the public transport choicecitations
  • 2014A continuous-time queueing model with class clustering and global FCFS service discipline10citations
  • 2011Road splits: smooth or rough passage?citations

Places of action

Chart of shared publication
Mélange, Willem
3 / 3 shared
Walraevens, Joris R R
1 / 1 shared
Walraevens, Joris
3 / 6 shared
Wittevrongel, Sabine
1 / 4 shared
Claeys, Dieter
2 / 3 shared
De Turck, Koen
2 / 2 shared
Fiems, Dieter
2 / 3 shared
Prabhu, B
1 / 1 shared
Van Den Bossche, Hannah
2 / 2 shared
Prabhu, Balakrishna
1 / 2 shared
Steyaert, Bart
1 / 1 shared
Chart of publication period
2022
2016
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Co-Authors (by relevance)

  • Mélange, Willem
  • Walraevens, Joris R R
  • Walraevens, Joris
  • Wittevrongel, Sabine
  • Claeys, Dieter
  • De Turck, Koen
  • Fiems, Dieter
  • Prabhu, B
  • Van Den Bossche, Hannah
  • Prabhu, Balakrishna
  • Steyaert, Bart

document

Discrete-time queues with variable service capacity: a basic model and its analysis

  • Walraevens, Joris
  • Bruneel, Herwig
  • Wittevrongel, Sabine
  • Claeys, Dieter
Abstract

In this paper, we present a basic discrete-time queueing model whereby the service process is decomposed in two (variable) components: the demand of each customer, expressed in a number of work units needed to provide full service of the customer, and the capacity of the server, i.e., the number of work units that the service facility is able to perform per time unit. The model is closely related to multi-server queueing models with server interruptions, in the sense that the service facility is able to deliver more than one unit of work per time unit, and that the number of work units that can be executed per time unit is not constant over time. Although multi-server queueing models with server interruptions—to some extent—allow us to study the concept of variable capacity, these models have a major disadvantage. The models are notoriously hard to analyze and even when explicit expressions are obtained, these contain various unknown probabilities that have to be calculated numerically, which makes the expressions difficult to interpret. For the model in this paper, on the other hand, we are able to obtain explicit closed-form expressions for the main performance measures of interest. Possible applications of this type of queueing model are numerous: the variable service capacity could model variable available bandwidths in communication networks, a varying production capacity in factories, a variable number of workers in an HR-environment, varying capacity in road traffic, etc.

Topics
  • customer
  • queuing
  • road
  • highway traffic
  • variable
  • production
  • employee
  • communication system

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