@article{
 title = {Simulation–optimization model for location of a public electric vehicle charging infrastructure},
 type = {article},
 year = {2013},
 identifiers = {[object Object]},
 keywords = {Charging infrastructure location,Electric vehicles,Vehicle charging},
 pages = {60-69},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S1361920913000345},
 month = {7},
 id = {dd96afb9-1e41-371c-b1af-d40450c45714},
 created = {2015-01-13T16:35:41.000Z},
 accessed = {2015-01-06},
 file_attached = {false},
 profile_id = {9696f304-db07-31d9-a8cd-d208939f9889},
 group_id = {062cfb24-9ce4-3a92-a41f-541a783d7b95},
 last_modified = {2017-03-09T15:29:23.010Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Xi2013},
 private_publication = {false},
 abstract = {The paper develops a simulation–optimization model that determines where to locate electric vehicle chargers to maximize their use by privately owned electric vehicles. Applying this model to the central-Ohio region, we demonstrate that a combination of level-one and -two chargers is preferable to level-two chargers only. We further explore interactions between the optimization criterion used and the budget available. We finally show that although the optimal location is sensitive to the specific optimization criterion considered, overall service levels are less sensitive to the optimization strategy.},
 bibtype = {article},
 author = {Xi, Xiaomin and Sioshansi, Ramteen and Marano, Vincenzo},
 journal = {Transportation Research Part D: Transport and Environment}
}

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