{"id":"https://openalex.org/W3113695437","doi":"https://doi.org/10.1109/itsc45102.2020.9294514","title":"Metro Train Timetable Rescheduling Based on Q-learning Approach","display_name":"Metro Train Timetable Rescheduling Based on Q-learning Approach","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3113695437","doi":"https://doi.org/10.1109/itsc45102.2020.9294514","mag":"3113695437"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294514","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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/A5008866335","display_name":"Boyi Su","orcid":"https://orcid.org/0000-0003-2104-2376"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyi Su","raw_affiliation_strings":["State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101896870","display_name":"Zhikai Wang","orcid":"https://orcid.org/0000-0003-0340-2999"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhikai Wang","raw_affiliation_strings":["State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038996257","display_name":"Shuai Su","orcid":"https://orcid.org/0000-0001-8412-9853"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Su","raw_affiliation_strings":["State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067908158","display_name":"Tao Tang","orcid":"https://orcid.org/0000-0001-7838-8525"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Tang","raw_affiliation_strings":["State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.3513,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.69652764,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9995999932289124,"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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9995999932289124,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.6649617552757263},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.6346795558929443},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.6305273771286011},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.5649729371070862},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5486300587654114},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5405762195587158},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4741624891757965},{"id":"https://openalex.org/keywords/decision-process","display_name":"Decision process","score":0.4442845582962036},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4189490079879761},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.39458411931991577},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3760250508785248},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2341431975364685},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11671975255012512}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6649617552757263},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.6346795558929443},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.6305273771286011},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.5649729371070862},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5486300587654114},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5405762195587158},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4741624891757965},{"id":"https://openalex.org/C2984634286","wikidata":"https://www.wikidata.org/wiki/Q1331926","display_name":"Decision process","level":2,"score":0.4442845582962036},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4189490079879761},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39458411931991577},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3760250508785248},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2341431975364685},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11671975255012512},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294514","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323067","display_name":"State Key Laboratory of Rail Traffic Control and Safety","ror":"https://ror.org/01yj56c84"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1643759343","https://openalex.org/W2031545009","https://openalex.org/W2045565802","https://openalex.org/W2109879495","https://openalex.org/W2134131633","https://openalex.org/W2414364427","https://openalex.org/W2514080459","https://openalex.org/W2533696363","https://openalex.org/W2572737592","https://openalex.org/W2938894022","https://openalex.org/W2976327234","https://openalex.org/W6768190797"],"related_works":["https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2413828414","https://openalex.org/W2367222340","https://openalex.org/W187740018","https://openalex.org/W2162286586","https://openalex.org/W4255368532","https://openalex.org/W4378501524","https://openalex.org/W1964650011"],"abstract_inverted_index":{"In":[0],"metro":[1,30],"system,":[2],"unpredictable":[3],"disturbances":[4],"influence":[5],"the":[6,29,39,44,58,67,77,90,101,110,123,126,137],"normal":[7],"operation":[8],"and":[9,50,93],"bring":[10],"much":[11],"inconvenience":[12],"to":[13,121],"passengers.":[14],"This":[15],"paper":[16],"focuses":[17],"on":[18],"train":[19,71],"timetable":[20],"rescheduling":[21,64],"(TTR)":[22],"problem":[23],"with":[24,61,87],"considering":[25],"practical":[26,63],"operations":[27],"in":[28],"management.":[31],"At":[32],"first,":[33],"an":[34,82],"optimization":[35,138],"model":[36,78],"that":[37,132],"takes":[38],"deviation":[40],"of":[41,48,113,125],"rescheduled":[42],"timetable,":[43],"total":[45],"delay":[46],"time":[47],"passengers":[49],"energy":[51],"consumption":[52],"as":[53],"objective":[54],"is":[55,79,97],"developed.":[56],"Meanwhile,":[57],"constraints,":[59],"together":[60],"some":[62,106],"rules":[65],"(e.g.,":[66],"preprogrammed":[68],"speed":[69],"profiles,":[70],"detention":[72],"strategy)":[73],"are":[74,118],"introduced.":[75],"Secondly,":[76],"reformulated":[80],"into":[81],"Markov":[83],"decision":[84],"process":[85],"(MDP)":[86],"well":[88],"defining":[89],"state,":[91],"action":[92],"reward":[94],"function,":[95],"which":[96],"then":[98],"solved":[99],"by":[100],"proposed":[102,127],"Q-learning":[103],"approach.":[104,128],"Finally,":[105],"case":[107],"studies":[108],"using":[109],"operational":[111],"data":[112],"Beijing":[114],"Yizhuang":[115],"Subway":[116],"Line":[117],"carried":[119],"out":[120],"demonstrate":[122],"effectiveness":[124],"The":[129],"results":[130],"indicate":[131],"a":[133,144],"tradeoff":[134],"solution":[135],"among":[136],"objectives":[139],"can":[140],"be":[141],"obtained":[142],"within":[143],"short":[145],"time.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}