{"id":"https://openalex.org/W4317460543","doi":"https://doi.org/10.1504/ijcistudies.2022.10053594","title":"Application of quantum-behaved characteristic particle swarm optimization algorithm in multi-objective optimization of urban rail train","display_name":"Application of quantum-behaved characteristic particle swarm optimization algorithm in multi-objective optimization of urban rail train","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4317460543","doi":"https://doi.org/10.1504/ijcistudies.2022.10053594"},"language":"en","primary_location":{"id":"doi:10.1504/ijcistudies.2022.10053594","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1504/ijcistudies.2022.10053594","pdf_url":null,"source":{"id":"https://openalex.org/S204065401","display_name":"International Journal of Computational Intelligence Studies","issn_l":"1755-4977","issn":["1755-4977","1755-4985"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Studies","raw_type":"journal-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/A5058156093","display_name":"Baodi Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126311","display_name":"Beijing Transportation Research Center","ror":"https://ror.org/03pydk223","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126311"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baodi Xiao","raw_affiliation_strings":["Beijing Kangjisen Transportation Technology Co., Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Kangjisen Transportation Technology Co., Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210126311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038604145","display_name":"Mingjian Su","orcid":null},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjian Su","raw_affiliation_strings":["School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101080469","display_name":"Lili Yue","orcid":null},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Yue","raw_affiliation_strings":["School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China","institution_ids":["https://openalex.org/I3133134087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.19939691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"3/4","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.8352000117301941,"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"}},"topics":[{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.8352000117301941,"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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.8159999847412109,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.7239000201225281,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7880880832672119},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7428063154220581},{"id":"https://openalex.org/keywords/multi-swarm-optimization","display_name":"Multi-swarm optimization","score":0.5828827023506165},{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.5828625559806824},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5757608413696289},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5133775472640991},{"id":"https://openalex.org/keywords/meta-optimization","display_name":"Meta-optimization","score":0.42772209644317627},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42524832487106323},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.4114108383655548},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11770448088645935},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08190152049064636}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7880880832672119},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7428063154220581},{"id":"https://openalex.org/C122357587","wikidata":"https://www.wikidata.org/wiki/Q6934508","display_name":"Multi-swarm optimization","level":3,"score":0.5828827023506165},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.5828625559806824},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5757608413696289},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5133775472640991},{"id":"https://openalex.org/C4935549","wikidata":"https://www.wikidata.org/wiki/Q6822261","display_name":"Meta-optimization","level":3,"score":0.42772209644317627},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42524832487106323},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.4114108383655548},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11770448088645935},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08190152049064636},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijcistudies.2022.10053594","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1504/ijcistudies.2022.10053594","pdf_url":null,"source":{"id":"https://openalex.org/S204065401","display_name":"International Journal of Computational Intelligence Studies","issn_l":"1755-4977","issn":["1755-4977","1755-4985"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Studies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2006324351","https://openalex.org/W2965421953","https://openalex.org/W2349895019","https://openalex.org/W2950423922","https://openalex.org/W2113650225","https://openalex.org/W2116074880","https://openalex.org/W2121780490","https://openalex.org/W2161494499","https://openalex.org/W2885739335","https://openalex.org/W2068415580"],"abstract_inverted_index":{"This":[0],"paper":[1],"combines":[2],"operation":[3,7],"control":[4,23,57,126,138],"strategy":[5,139],"and":[6,16,43,65,80,119,130],"curve":[8],"to":[9,72,103],"address":[10],"the":[11,28,31,74,81,85,92,96,105,111,122,131,135,146],"problems":[12],"of":[13,20,84,95],"frequent":[14],"switching":[15],"high":[17],"energy":[18,44],"consumption":[19],"traditional":[21],"ATO":[22],"policies.":[24],"Firstly,":[25],"based":[26,37],"on":[27,38,145],"Pareto":[29],"principle,":[30],"objective":[32],"optimisation":[33,52,82,143],"model":[34],"is":[35,59,89],"established":[36],"urban":[39],"rail":[40],"trains'":[41],"punctuality":[42],"consumption.":[45],"Then,":[46],"a":[47,141],"multi-objective":[48],"quantum":[49],"particle":[50],"swarm":[51],"(MOQPSO)":[53],"algorithm":[54,88,113],"with":[55],"fewer":[56],"parameters":[58],"adopted.":[60],"The":[61],"Gaussian":[62],"mutation":[63],"operator":[64],"crowding":[66],"distance":[67],"sorting":[68],"method":[69],"are":[70,101,128],"introduced":[71],"select":[73],"global":[75],"optimal":[76],"guidance":[77],"particles":[78],"better,":[79],"effect":[83,144],"conventional":[86],"MOPSO":[87],"compared.":[90],"Finally,":[91],"actual":[93],"data":[94],"Beijing":[97],"Subway":[98],"Yizhuang":[99],"Line":[100],"used":[102],"verify":[104],"algorithm.":[106],"Simulation":[107],"results":[108,132],"show":[109,133],"that":[110,134],"MOQPSO":[112],"has":[114,140],"advantages":[115],"in":[116],"convergence,":[117],"diversity,":[118],"optimisation.":[120],"At":[121],"same":[123],"time,":[124],"different":[125],"strategies":[127],"compared,":[129],"improved":[136],"hybrid":[137],"better":[142],"longer":[147],"line.":[148]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
