{"id":"https://openalex.org/W4206658781","doi":"https://doi.org/10.1109/ieem50564.2021.9672810","title":"A Reinforcement Learning Approach for Optimization of E-bus Off-normal Schedule with Time Windows","display_name":"A Reinforcement Learning Approach for Optimization of E-bus Off-normal Schedule with Time Windows","publication_year":2021,"publication_date":"2021-12-13","ids":{"openalex":"https://openalex.org/W4206658781","doi":"https://doi.org/10.1109/ieem50564.2021.9672810"},"language":"en","primary_location":{"id":"doi:10.1109/ieem50564.2021.9672810","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem50564.2021.9672810","pdf_url":null,"source":{"id":"https://openalex.org/S4363607822","display_name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101451442","display_name":"Jiguang Wang","orcid":"https://orcid.org/0009-0005-3034-1871"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiguang Wang","raw_affiliation_strings":["Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653787","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0001-5526-866X"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061328883","display_name":"Xinglu Liu","orcid":"https://orcid.org/0000-0001-6011-3179"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinglu Liu","raw_affiliation_strings":["Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108043491","display_name":"Zhide Li","orcid":"https://orcid.org/0009-0004-0387-4448"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhide Li","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jinhui Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinhui Wen","raw_affiliation_strings":["Shenzhen Intelligent Public Transportation Technology Co., Ltd, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Intelligent Public Transportation Technology Co., Ltd, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108743840","display_name":"Wai Kin Victor Chan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wai Kin Chan","raw_affiliation_strings":["Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transportation and Logistics Systems Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24410933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"558","last_page":"562"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":1.0,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9997000098228455,"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/T10524","display_name":"Traffic control and management","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.7113821506500244},{"id":"https://openalex.org/keywords/trips-architecture","display_name":"TRIPS architecture","score":0.6993590593338013},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6839134693145752},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.6558799147605896},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6328030824661255},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5775163173675537},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.4907418489456177},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.4409600794315338},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43128663301467896},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.3892569839954376},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.37818390130996704},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3275964856147766},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21264880895614624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11929038166999817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1044096052646637}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7113821506500244},{"id":"https://openalex.org/C157085824","wikidata":"https://www.wikidata.org/wiki/Q2384809","display_name":"TRIPS architecture","level":2,"score":0.6993590593338013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6839134693145752},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.6558799147605896},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6328030824661255},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5775163173675537},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.4907418489456177},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.4409600794315338},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43128663301467896},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3892569839954376},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.37818390130996704},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3275964856147766},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21264880895614624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11929038166999817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1044096052646637},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem50564.2021.9672810","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem50564.2021.9672810","pdf_url":null,"source":{"id":"https://openalex.org/S4363607822","display_name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G6298785130","display_name":"\u591a\u5c42\u793e\u4f1a\u7f51\u7edc\u5728\u9690\u79c1\u4fdd\u62a4\u6761\u4ef6\u4e0b\u7684\u5efa\u6a21\u53ca\u7279\u6027\u7814\u7a76\u4e0e\u5e94\u7528","funder_award_id":"71971127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1741383983","https://openalex.org/W2031128290","https://openalex.org/W2078895652","https://openalex.org/W2550584736","https://openalex.org/W2558600380","https://openalex.org/W2790213249","https://openalex.org/W2798885736","https://openalex.org/W2904681300","https://openalex.org/W2997842726","https://openalex.org/W3011120880","https://openalex.org/W3016204439","https://openalex.org/W3123589737","https://openalex.org/W3145044386","https://openalex.org/W3179601372"],"related_works":["https://openalex.org/W4400868993","https://openalex.org/W3096874164","https://openalex.org/W1985560493","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2145363145","https://openalex.org/W1626977535","https://openalex.org/W2341346307","https://openalex.org/W3168977894","https://openalex.org/W2315999538"],"abstract_inverted_index":{"The":[0,93],"lack":[1],"of":[2,12,36,38,44,56,95],"traffic":[3],"capacity":[4],"during":[5],"peak":[6],"hours":[7],"is":[8,53,98,126,141],"an":[9,86],"emerging":[10],"problem":[11,89,97,125],"modern":[13],"urban":[14],"transportation.":[15],"This":[16],"has":[17],"prompted":[18],"some":[19],"bus":[20,104],"companies":[21],"to":[22,31,67,99],"propose":[23,85],"E-bus":[24,27,45],"service":[25],"model.":[26],"was":[28],"originally":[29],"intended":[30],"serve":[32],"the":[33,42,57,63,69,74,101,110,122,150,160],"commuting":[34],"tasks":[35],"employees":[37],"other":[39],"companies.":[40],"However,":[41],"trips":[43],"are":[46],"relatively":[47],"fixed":[48],"and":[49,72,119,132,158],"single-trip,":[50],"so":[51],"e-bus":[52],"idle":[54],"most":[55],"time.":[58],"Therefore,":[59],"we":[60,83],"put":[61],"forward":[62],"off-normal":[64,87],"schedule":[65,88],"strategy":[66],"improve":[68],"transport":[70,75],"efficiency":[71],"reduce":[73],"pressure":[76],"on":[77,137],"busy":[78],"lines.":[79],"In":[80],"this":[81,96,147],"work,":[82],"first":[84],"with":[90],"time":[91],"windows.":[92],"objective":[94],"determine":[100],"optimal":[102,151],"shared":[103],"scheduling,":[105],"reducing":[106],"empty":[107],"trips,":[108],"increasing":[109],"total":[111],"revenue.":[112],"By":[113],"defining":[114],"state":[115],"characteristics,":[116],"action":[117],"space":[118],"reward":[120],"function,":[121],"proposed":[123],"scheduling":[124,134],"formulated":[127],"as":[128],"Markov":[129],"decision":[130],"process,":[131],"a":[133],"method":[135,148],"based":[136],"multi-agent":[138],"reinforcement":[139],"learning":[140],"developed.":[142],"Simulation":[143],"results":[144],"show":[145],"that":[146],"learns":[149],"or":[152],"near-optimal":[153],"solution":[154],"from":[155],"previous":[156],"experience":[157],"improves":[159],"revenue":[161],"significantly.":[162]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}