Large-scale test data set for location problems-Reference-Cited by-同舟云学术

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Large-scale test data set for location problems

Published:2018-04 Issue: Volume:17 Page:267-274
ISSN:2352-3409
Container-title:Data in Brief
language:en
Short-container-title:Data in Brief

Author:

Cebecauer Matej,Buzna Ľuboš

Funder

FP 7 project ERAdiate

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference4 articles.

1. A versatile adaptive aggregation framework for spatially large discrete location-allocation problems;Cebecauer;Comput. Ind. Eng.,2017

2. Effects of demand estimates on the evaluation and optimality of service centre locations;Cebecauer;Int. J. Geogr. Inf. Sci.,2016

3. 〈https://www.openstreetmap.org/〉.

4. C. Jacobs-Crisioni, C. Lavalle, European Population Map 2006. European Commission, Joint Research Centre (JRC) [Dataset] PID: 〈http://data.europa.eu/89h/jrc-luisa-europopmap06〉, 2016.

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1. An attention model with multiple decoders for solving p-Center problems;International Journal of Applied Earth Observation and Geoinformation;2023-12

2. Solving uncapacitated P-Median problem with reinforcement learning assisted by graph attention networks;Applied Intelligence;2022-05-04

3. Covering problems with polyellipsoids: A location analysis perspective;European Journal of Operational Research;2021-02

4. Bi-objective multi-layer location–allocation model for the immediate aftermath of sudden-onset disasters;Transportation Research Part E: Logistics and Transportation Review;2019-07

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