Publikation: Enabling E-Mobility: Facility Location for Battery Loading Stations
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2013
Autor:innen
Funke, Stefan
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NPProceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence. Menlo Park, CA, USA: AAAI Publications, 2013, pp. 1341-1347
Zusammenfassung
The short cruising range due to the limited battery supply of current Electric Vehicles (EVs) is one of the main obstacles for a complete transition to E-mobility. Until batteries of higher energy storage density have been developed, it is of utmost importance to deliberately plan the locations of new loading stations for best possible coverage. Ideally the network of loading stations should allow driving from anywhere to anywhere (and back) without running out of energy. We show that minimizing the number of necessary loading stations to achieve this goal is NP-hard and even worse, we can rule out polynomial-time constant approximation algorithms. Hence algorithms with better approximation guarantees have to make use of the special structure of road networks (which is not obvious how to do it). On the positive side, we show with instance based lower bounds that our heuristic algorithms achieve provably good solutions on real-world problem instances.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
E-Mobility, Inapproximability, Heuristic Search
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The Twenty-Seventh AAAI Conference on Artificial Intelligence, 14. Juli 2013 - 18. Juli 2013, Bellevue, WA, USA
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STORANDT, Sabine, Stefan FUNKE, 2013. Enabling E-Mobility: Facility Location for Battery Loading Stations. The Twenty-Seventh AAAI Conference on Artificial Intelligence. Bellevue, WA, USA, 14. Juli 2013 - 18. Juli 2013. In: NPProceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence. Menlo Park, CA, USA: AAAI Publications, 2013, pp. 1341-1347BibTex
@inproceedings{Storandt2013Enabl-46623,
year={2013},
title={Enabling E-Mobility: Facility Location for Battery Loading Stations},
url={https://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6239},
publisher={AAAI Publications},
address={Menlo Park, CA, USA},
booktitle={NPProceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence},
pages={1341--1347},
author={Storandt, Sabine and Funke, Stefan}
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<dcterms:abstract xml:lang="eng">The short cruising range due to the limited battery supply of current Electric Vehicles (EVs) is one of the main obstacles for a complete transition to E-mobility. Until batteries of higher energy storage density have been developed, it is of utmost importance to deliberately plan the locations of new loading stations for best possible coverage. Ideally the network of loading stations should allow driving from anywhere to anywhere (and back) without running out of energy. We show that minimizing the number of necessary loading stations to achieve this goal is NP-hard and even worse, we can rule out polynomial-time constant approximation algorithms. Hence algorithms with better approximation guarantees have to make use of the special structure of road networks (which is not obvious how to do it). On the positive side, we show with instance based lower bounds that our heuristic algorithms achieve provably good solutions on real-world problem instances.</dcterms:abstract>
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2019-08-07
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