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The problem of optimally scheduling the charging demand of electric vehicles within the constraints of the electricity infrastructure is called the charge scheduling problem. The models of the charging speed, horizon, and charging demand determine the computational complexity of the charge scheduling problem. We show that for about 20 variants the problem is either in P or weakly NP-hard and dynamic programs exist to compute optimal solutions. About 10 other variants of the problem are strongly NP-hard, presenting a potentially significant obstacle to their use in practical situations of scale. An experimental study establishes up to what parameter values the dynamic programs can determine optimal solutions in a couple of minutes.
|Title of host publication||Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)|
|Publisher||International Joint Conferences on Artifical Intelligence (IJCAI)|
|Number of pages||7|
|Publication status||Published - 13 Jul 2018|
|Event||IJCAI 2018: 27th International Joint Conference on Artificial Intelligence - Stockholm, Sweden|
Duration: 13 Jul 2018 → 19 Jul 2018
Conference number: 27
|Period||13/07/18 → 19/07/18|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
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1/02/17 → 15/09/19