A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00347214" target="_blank" >RIV/68407700:21230/20:00347214 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-64984-5_7" target="_blank" >https://doi.org/10.1007/978-3-030-64984-5_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-64984-5_7" target="_blank" >10.1007/978-3-030-64984-5_7</a>
Alternative languages
Result language
angličtina
Original language name
A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions
Original language description
In order to keep roads in acceptable condition, and to perform maintenance of essential infrastructure, roadworks are required. Due to the increasing traffic volumes and the increasing urbanisation, road agencies are currently facing the problem of effective planning frequent –and usually concurrent– roadworks in the controlled region. However, there is a lack of techniques that can support traffic authorities in this task. In fact, traffic authorities have usually to rely on human experts (and their intuition) to decide how to schedule and perform roadworks. In this paper, we introduce a Mixed-Integer Programming approach that can be used by traffic authorities to plan a set of required roadworks, over a period of time, in a large urban region, by specifying constraints to be satisfied and suitable quality metrics.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA18-07252S" target="_blank" >GA18-07252S: MoRePlan: Modeling and Reformulating Planning Problems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
AI 2020: Advances in Artificial Intelligence
ISBN
978-3-030-64983-8
ISSN
0302-9743
e-ISSN
0302-9743
Number of pages
12
Pages from-to
82-93
Publisher name
Springer
Place of publication
Cham
Event location
Canberra
Event date
Nov 29, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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