{"id":"https://openalex.org/W4412403878","doi":"https://doi.org/10.1109/access.2025.3588880","title":"Fairness-Oriented Charging Station Location Optimization Driven by Deep Reinforcement Learning","display_name":"Fairness-Oriented Charging Station Location Optimization Driven by Deep Reinforcement Learning","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412403878","doi":"https://doi.org/10.1109/access.2025.3588880"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3588880","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3588880","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3588880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Siyue Yuan","orcid":"https://orcid.org/0009-0001-6275-0478"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Siyue Yuan","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-6275-0478","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiaying Fu","orcid":"https://orcid.org/0009-0002-5567-4435"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaying Fu","raw_affiliation_strings":["School of Remote Sensing Information Engineering, Wuhan University, Wuhan, Hubei, China","School of Remote Sensing Information Engineering, Wuhan University, Wuhan, Hubei Province, China"],"raw_orcid":"https://orcid.org/0009-0002-5567-4435","affiliations":[{"raw_affiliation_string":"School of Remote Sensing Information Engineering, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Remote Sensing Information Engineering, Wuhan University, Wuhan, Hubei Province, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113277803","display_name":"Xiaoyin Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyin Ma","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-4419-7479","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.8757,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.86547632,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"125217","last_page":"125231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9427000284194946,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12222","display_name":"IoT-based Smart Home Systems","score":0.9315000176429749,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7902301549911499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7049815654754639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32466161251068115}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7902301549911499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049815654754639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32466161251068115}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3588880","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3588880","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:31d2e5d994714228a746097e285b8941","is_oa":true,"landing_page_url":"https://doaj.org/article/31d2e5d994714228a746097e285b8941","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 125217-125231 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3588880","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3588880","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2023397213","https://openalex.org/W2050000782","https://openalex.org/W2904489117","https://openalex.org/W2906791301","https://openalex.org/W3054502679","https://openalex.org/W3120760878","https://openalex.org/W3123542798","https://openalex.org/W3184227953","https://openalex.org/W4205365152","https://openalex.org/W4213179779","https://openalex.org/W4284674589","https://openalex.org/W4289745910","https://openalex.org/W4308277370","https://openalex.org/W4308906917","https://openalex.org/W4322745724","https://openalex.org/W4382517943","https://openalex.org/W4386011141","https://openalex.org/W4388694357","https://openalex.org/W4388844140","https://openalex.org/W4389592736","https://openalex.org/W4390344718","https://openalex.org/W4390397349","https://openalex.org/W4391442378","https://openalex.org/W4391989010","https://openalex.org/W4392094223","https://openalex.org/W4392354700","https://openalex.org/W4396716309","https://openalex.org/W4399496964","https://openalex.org/W4400219755","https://openalex.org/W4400620865","https://openalex.org/W4404219992","https://openalex.org/W4404644664","https://openalex.org/W4405664849","https://openalex.org/W4405824837","https://openalex.org/W4408279012"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4306904969","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2138720691","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Against":[0],"the":[1,32,50,74,97,101,120,135,168,190,202,223,250,261],"backdrop":[2],"of":[3,34,53,61,77,122,170,235,263],"growing":[4],"global":[5],"attention":[6],"to":[7,25,42,94,96,106,118,133,156,166,188],"sustainable":[8],"development":[9],"and":[10,67,87,110,146,151,181,218,239,242,246,257],"environmental":[11],"protection,":[12],"electric":[13,78],"vehicles":[14],"(EVs)":[15],"have":[16],"become":[17],"an":[18,43,59],"important":[19],"choice":[20],"for":[21,46,260],"green":[22,136],"transportation":[23,137],"due":[24],"their":[26],"zero-emission":[27],"advantage.":[28],"In":[29],"recent":[30],"years,":[31],"number":[33],"EVs":[35],"in":[36,63,70,100,112,125,206,233,267],"Beijing":[37,207],"has":[38],"rapidly":[39],"increased,":[40],"leading":[41],"urgent":[44],"demand":[45],"charging":[47,54,123,203,265],"infrastructure.":[48],"However,":[49],"existing":[51],"layout":[52,121,205],"stations":[55,62,124],"is":[56,154,179,186],"imbalanced,":[57],"with":[58,130,215],"over-concentration":[60],"central":[64],"urban":[65],"areas":[66],"insufficient":[68],"coverage":[69,129,177,236],"peripheral":[71],"regions,":[72],"hindering":[73],"further":[75],"promotion":[76],"vehicles.":[79],"Existing":[80],"studies":[81],"mostly":[82],"rely":[83],"on":[84],"static":[85],"data":[86,141],"traditional":[88,196,231],"optimization":[89,240],"methods,":[90],"which":[91],"are":[92,149,163],"unable":[93],"adapt":[95],"dynamic":[98],"changes":[99],"city,":[102],"necessitating":[103],"innovative":[104],"strategies":[105],"improve":[107],"both":[108],"fairness":[109,132,247],"efficiency":[111],"location":[113],"planning.":[114],"This":[115,253],"study":[116,254],"aims":[117],"optimize":[119],"Beijing,":[126],"balancing":[127],"overall":[128],"regional":[131],"support":[134],"system.":[138],"First,":[139],"multi-source":[140],"including":[142],"POI,":[143],"population,":[144],"GDP,":[145],"traffic":[147],"networks":[148],"integrated,":[150],"GIS":[152],"technology":[153],"used":[155,165],"analyze":[157],"spatial":[158],"distribution":[159],"characteristics.":[160],"Geographic":[161],"detectors":[162],"then":[164],"quantify":[167],"weight":[169],"influencing":[171],"factors.":[172,226],"Next,":[173],"a":[174,209],"fairness-oriented":[175],"maximum":[176],"model":[178],"constructed,":[180],"Deep":[182],"Reinforcement":[183],"Learning":[184],"(DRL)":[185],"employed":[187],"solve":[189],"problem,":[191],"evaluating":[192],"its":[193],"advantages":[194],"over":[195],"methods.":[197],"The":[198,227],"results":[199],"show":[200],"that":[201],"station":[204],"exhibits":[208],"\"dense":[210],"center,":[211],"sparse":[212],"periphery\"":[213],"pattern,":[214],"schools,":[216],"hospitals,":[217],"other":[219],"public":[220],"facilities":[221],"being":[222],"main":[224],"driving":[225],"DRL":[228],"approach":[229],"outperforms":[230],"methods":[232],"terms":[234],"rate,":[237],"fairness,":[238],"efficiency,":[241],"can":[243],"balance":[244],"benefits":[245],"by":[248],"adjusting":[249],"parameter":[251],"\u03bb":[252],"provides":[255],"theoretical":[256],"practical":[258],"guidance":[259],"planning":[262],"EV":[264],"infrastructure":[266],"Beijing.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
