{"id":"https://openalex.org/W4312811104","doi":"https://doi.org/10.1109/case49997.2022.9926504","title":"The AGV Battery Swapping Policy Based on Reinforcement Learning","display_name":"The AGV Battery Swapping Policy Based on Reinforcement Learning","publication_year":2022,"publication_date":"2022-08-20","ids":{"openalex":"https://openalex.org/W4312811104","doi":"https://doi.org/10.1109/case49997.2022.9926504"},"language":"en","primary_location":{"id":"doi:10.1109/case49997.2022.9926504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case49997.2022.9926504","pdf_url":null,"source":{"id":"https://openalex.org/S4363607892","display_name":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109360758","display_name":"Min Seok Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Min Seok Lee","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology,Department of Industrial and Systems Engineering,Daejeon,Republic of Korea,34141"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology,Department of Industrial and Systems Engineering,Daejeon,Republic of Korea,34141","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012203130","display_name":"Young Jae Jang","orcid":"https://orcid.org/0000-0002-2342-1444"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young Jae Jang","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology,Department of Industrial and Systems Engineering,Daejeon,Republic of Korea,34141"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology,Department of Industrial and Systems Engineering,Daejeon,Republic of Korea,34141","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5109360758"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.6929,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63152437,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1479","last_page":"1484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9736999869346619,"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":0.8699220418930054},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.7675886750221252},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.6111129522323608},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.5989533066749573},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5565085411071777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5230879783630371},{"id":"https://openalex.org/keywords/swap","display_name":"Swap (finance)","score":0.4715411961078644},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4296761453151703},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3695661425590515},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.2965400815010071},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2681563198566437}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8699220418930054},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7675886750221252},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.6111129522323608},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.5989533066749573},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5565085411071777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5230879783630371},{"id":"https://openalex.org/C99821215","wikidata":"https://www.wikidata.org/wiki/Q1136583","display_name":"Swap (finance)","level":2,"score":0.4715411961078644},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4296761453151703},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3695661425590515},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2965400815010071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2681563198566437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case49997.2022.9926504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case49997.2022.9926504","pdf_url":null,"source":{"id":"https://openalex.org/S4363607892","display_name":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4400868993","https://openalex.org/W3096874164","https://openalex.org/W1985560493","https://openalex.org/W2937181779","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2145363145","https://openalex.org/W1626977535","https://openalex.org/W2341346307","https://openalex.org/W3168977894"],"abstract_inverted_index":{"The":[0,87,105],"automated":[1,9],"guided":[2],"vehicle":[3,53],"(AGV),":[4],"a":[5,28,46,52,57,95,122],"typical":[6],"form":[7],"of":[8,39,79,89,135,143,157],"material":[10],"handling":[11],"system,":[12],"generally":[13],"utilizes":[14,121],"electric":[15],"power":[16],"from":[17],"an":[18],"internally":[19],"mounted":[20],"battery":[21,29,34,58,61],"pack.":[22],"AGVs":[23],"need":[24],"to":[25,35,56,93,98,138],"occasionally":[26],"visit":[27],"station":[30,59],"and":[31,72,117,120,127,162],"swap":[32],"the":[33,77,100,133,140,144,155,158,163],"manage":[36],"their":[37],"state":[38],"charge.":[40],"An":[41],"AGV":[42,101,170],"system":[43,102],"therefore":[44],"needs":[45],"swapping":[47,68,96,107,146,160],"policy,":[48,161],"which":[49,82],"determines":[50],"when":[51],"should":[54],"proceed":[55],"for":[60,169],"replacement.":[62],"In":[63],"real":[64],"industrial":[65],"practice,":[66],"most":[67],"policies":[69],"are":[70,73],"conservative":[71],"based":[74,110],"heuristically":[75],"on":[76,111],"experiences":[78],"decision":[80,124],"makers,":[81],"results":[83,134,164],"in":[84],"production":[85,103],"inefficiency.":[86],"objective":[88],"this":[90],"research":[91],"is":[92,109],"develop":[94],"strategy":[97],"improve":[99],"efficiency.":[104],"proposed":[106,145,159],"policy":[108,147],"sequential":[112],"decisions":[113],"that":[114],"consider":[115],"current":[116],"future":[118],"situations,":[119],"Markov":[123],"process":[125],"framework":[126],"deep":[128],"reinforcement":[129],"learning.":[130],"We":[131,152],"present":[132],"numerical":[136],"experiments":[137],"demonstrate":[139,165],"superior":[141],"performance":[142],"compared":[148],"with":[149],"heuristic":[150],"policies.":[151],"also":[153],"analyze":[154],"properties":[156],"its":[166],"application":[167],"potential":[168],"systems.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}