{"id":"https://openalex.org/W4392152354","doi":"https://doi.org/10.1109/globecom54140.2023.10437362","title":"FAG-scheduler: Privacy-Preserving Federated Reinforcement Learning with GRU for Production Scheduling on Automotive Manufacturing","display_name":"FAG-scheduler: Privacy-Preserving Federated Reinforcement Learning with GRU for Production Scheduling on Automotive Manufacturing","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4392152354","doi":"https://doi.org/10.1109/globecom54140.2023.10437362"},"language":"en","primary_location":{"id":"doi:10.1109/globecom54140.2023.10437362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","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/A5100634408","display_name":"Jinhua Chen","orcid":"https://orcid.org/0000-0003-0209-8913"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Jinhua Chen","raw_affiliation_strings":["Graduate School of Science and Engineering, Hosei University,Tokyo,Japan,184-8584"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Hosei University,Tokyo,Japan,184-8584","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076994242","display_name":"Keping Yu","orcid":"https://orcid.org/0000-0001-5735-2507"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keping Yu","raw_affiliation_strings":["Graduate School of Science and Engineering, Hosei University,Tokyo,Japan,184-8584","RIKEN Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Hosei University,Tokyo,Japan,184-8584","institution_ids":["https://openalex.org/I204291657"]},{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076776322","display_name":"Joel J. P. C. Rodrigues","orcid":"https://orcid.org/0000-0001-8657-3800"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joel J. P. C. Rodrigues","raw_affiliation_strings":["Lus&#x00F3;fona University,COPELABS,Lisbon,Portugal"],"affiliations":[{"raw_affiliation_string":"Lus&#x00F3;fona University,COPELABS,Lisbon,Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057916222","display_name":"Mohsen Guizani","orcid":"https://orcid.org/0000-0002-8972-8094"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Mohsen Guizani","raw_affiliation_strings":["Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI),Machine Learning Department,UAE","Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), UAE"],"affiliations":[{"raw_affiliation_string":"Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI),Machine Learning Department,UAE","institution_ids":["https://openalex.org/I4210113480"]},{"raw_affiliation_string":"Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), UAE","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101848699","display_name":"Takuro Sato","orcid":"https://orcid.org/0000-0002-1172-8131"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuro Sato","raw_affiliation_strings":["Research Institute for Science and Engineering, Waseda University,Tokyo,Japan","Research Institute for Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Research Institute for Science and Engineering, Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Research Institute for Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100634408"],"corresponding_institution_ids":["https://openalex.org/I204291657"],"apc_list":null,"apc_paid":null,"fwci":0.9189,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82438375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5147","last_page":"5152"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.958299994468689,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10763","display_name":"Digital Transformation in Industry","score":0.9090999960899353,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.760665774345398},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6998034715652466},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6958277225494385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6932464838027954},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.41845089197158813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21178165078163147},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13052421808242798},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.08054730296134949}],"concepts":[{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.760665774345398},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6998034715652466},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6958277225494385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6932464838027954},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.41845089197158813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21178165078163147},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13052421808242798},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.08054730296134949},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom54140.2023.10437362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2608702473","https://openalex.org/W2807766588","https://openalex.org/W3036339940","https://openalex.org/W3038822267","https://openalex.org/W3180608480","https://openalex.org/W3202110028","https://openalex.org/W3205598877","https://openalex.org/W3209696639","https://openalex.org/W4290189424","https://openalex.org/W4290189483","https://openalex.org/W4312594094","https://openalex.org/W4313259395","https://openalex.org/W4315629633","https://openalex.org/W4323896969","https://openalex.org/W6692846177"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4382644535","https://openalex.org/W2522768275","https://openalex.org/W2352938035","https://openalex.org/W2390279801","https://openalex.org/W4306904969","https://openalex.org/W2351672553","https://openalex.org/W2373392303"],"abstract_inverted_index":{"The":[0,68],"automotive":[1],"manufacturing":[2,83],"industry":[3],"faces":[4],"challenges":[5],"in":[6,17,73],"production":[7],"planning,":[8],"but":[9],"current":[10],"heuristic":[11],"algorithms":[12],"and":[13,19,51,77],"solvers":[14],"have":[15],"limitations":[16],"scalability":[18],"local":[20],"optima.":[21],"Moreover,":[22],"data":[23,62],"security":[24,63],"concerns":[25],"are":[26],"often":[27],"overlooked.":[28],"To":[29],"address":[30],"these":[31],"issues,":[32],"this":[33],"paper":[34],"introduces":[35],"the":[36],"FAG-Scheduler,":[37],"a":[38],"federated":[39,52],"reinforcement":[40],"learning":[41],"approach":[42],"integrating":[43],"asynchronous":[44],"advantage":[45],"actor-critic,":[46],"gated":[47],"recurrent":[48],"unit":[49],"algorithms,":[50],"learning.":[53],"By":[54],"sharing":[55],"model":[56],"parameters":[57],"instead":[58],"of":[59],"raw":[60],"data,":[61],"is":[64],"ensured":[65],"among":[66],"participants.":[67],"FAG-Scheduler":[69],"achieves":[70],"optimal":[71],"solutions":[72],"under":[74],"5":[75],"seconds":[76],"demonstrates":[78],"high":[79],"adaptability":[80],"to":[81],"other":[82],"contexts.":[84],"It":[85],"presents":[86],"potential":[87],"applications":[88],"with":[89],"significant":[90],"improvements":[91],"over":[92],"conventional":[93],"methods.":[94]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
