{"id":"https://openalex.org/W3100691142","doi":"https://doi.org/10.3233/faia200752","title":"Optimization of Transit Scheduling Combined with Short-Turn Service Based on Real-Time Passenger Flow","display_name":"Optimization of Transit Scheduling Combined with Short-Turn Service Based on Real-Time Passenger Flow","publication_year":2020,"publication_date":"2020-11-09","ids":{"openalex":"https://openalex.org/W3100691142","doi":"https://doi.org/10.3233/faia200752","mag":"3100691142"},"language":"en","primary_location":{"id":"doi:10.3233/faia200752","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia200752","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200752","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200752","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072443313","display_name":"Ailing Huang","orcid":"https://orcid.org/0000-0002-9948-6463"},"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":true,"raw_author_name":"Ailing Huang","raw_affiliation_strings":["Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000515156","display_name":"Yijing Miao","orcid":null},"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":"Yijing Miao","raw_affiliation_strings":["Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100414550","display_name":"Jiarui Li","orcid":"https://orcid.org/0009-0004-7658-912X"},"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":"Jiarui Li","raw_affiliation_strings":["Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China","STV Inc, Los Angeles, CA 90017, U.S.A","Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China; STV Inc, Los Angeles, CA 90017, U.S.A"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"STV Inc, Los Angeles, CA 90017, U.S.A","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of comprehensive transportation big data application technology, Beijing Jiaotong University, Beijing 100044, P.R.China; STV Inc, Los Angeles, CA 90017, U.S.A","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072443313"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29155206,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9991999864578247,"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":0.9991999864578247,"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":0.989300012588501,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9682999849319458,"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/beijing","display_name":"Beijing","score":0.773338258266449},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6906399726867676},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.5705400109291077},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.41949722170829773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4116702079772949},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.37613290548324585},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3612542748451233},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33769434690475464},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.337588369846344},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.21627816557884216}],"concepts":[{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.773338258266449},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6906399726867676},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.5705400109291077},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.41949722170829773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4116702079772949},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.37613290548324585},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3612542748451233},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33769434690475464},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.337588369846344},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.21627816557884216},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia200752","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia200752","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200752","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia200752","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia200752","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200752","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.550000011920929,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3100691142.pdf","grobid_xml":"https://content.openalex.org/works/W3100691142.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W598095728","https://openalex.org/W1471495039","https://openalex.org/W2058358442","https://openalex.org/W2084750728","https://openalex.org/W2092396569","https://openalex.org/W2120499477","https://openalex.org/W2379579777","https://openalex.org/W2383899005","https://openalex.org/W2462365036","https://openalex.org/W2582920180","https://openalex.org/W2606327058","https://openalex.org/W2735409613","https://openalex.org/W2790131133","https://openalex.org/W2796088329","https://openalex.org/W2802971719","https://openalex.org/W2905256011","https://openalex.org/W2955031369","https://openalex.org/W3087141152","https://openalex.org/W3151810850"],"related_works":["https://openalex.org/W2015747722","https://openalex.org/W2362050182","https://openalex.org/W2382418233","https://openalex.org/W2369897927","https://openalex.org/W3031731056","https://openalex.org/W4293167957","https://openalex.org/W2361035307","https://openalex.org/W2380455807","https://openalex.org/W2993975634","https://openalex.org/W2367835030"],"abstract_inverted_index":{"In":[0],"view":[1],"of":[2,5,14,22,59,82,94,104,110,158],"a":[3,45,63,147],"series":[4],"problems,":[6],"such":[7],"as":[8,134],"unable":[9],"to":[10,65],"meet":[11],"the":[12,32,37,56,67,79,84,90,96,101,118,123,139,155,171,176,184,192],"needs":[13],"passengers,":[15,95],"high":[16],"full":[17],"load":[18],"ratio":[19],"or":[20],"waste":[21],"carrying":[23],"capacity":[24],"on":[25,55],"unbalanced":[26],"passenger":[27,60,141],"flow":[28,61,142],"sections":[29],"caused":[30],"by":[31,117,187],"all-stop":[33,113,173],"fleet":[34,174,185],"scheduling":[35,48,120,162,181],"in":[36,146],"urban":[38],"public":[39,105],"transit":[40,106],"system,":[41],"this":[42],"paper":[43],"proposed":[44],"bus":[46,132],"combination":[47,161,180],"strategy":[49],"with":[50,78,170],"considering":[51],"short-turn":[52,111,159,178],"service":[53,160,179],"based":[54],"imbalance":[57],"coefficient":[58],"and":[62,100,112,122,143,152,154,189,195],"method":[64,125],"determine":[66],"turning":[68],"back":[69],"point.":[70],"A":[71,131],"combined":[72,119],"dispatching":[73],"optimization":[74],"model":[75],"is":[76,126,163],"established":[77],"objective":[80],"function":[81],"minimizing":[83],"total":[85],"system":[86,196],"cost":[87,93,99,103],"which":[88],"includes":[89],"waiting":[91],"time":[92],"congestion":[97],"feeling":[98],"operation":[102,193],"enterprises.":[107],"The":[108,165],"headways":[109],"scheme":[114,157],"are":[115,150],"optimized":[116,156,177],"model,":[121],"solution":[124],"proposed.":[127],"Taking":[128],"Beijing":[129],"No.":[130],"line":[133],"an":[135],"empirical":[136],"analysis":[137],"object,":[138],"real-time":[140],"vehicle":[144],"data":[145],"working":[148],"day":[149],"collected":[151],"analyzed,":[153],"obtained.":[164],"results":[166],"show":[167],"that":[168],"compared":[169],"traditional":[172],"scheduling,":[175],"can":[182],"reduce":[183],"size":[186],"4.9%":[188],"effectively":[190],"improve":[191],"efficiency":[194],"benefits.":[197]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}