{"id":"https://openalex.org/W4294811484","doi":"https://doi.org/10.1109/cec55065.2022.9870309","title":"Optimal Production Scheduling using a Production Simulator and Multi-population Global-best Modified Brain Storm Optimization","display_name":"Optimal Production Scheduling using a Production Simulator and Multi-population Global-best Modified Brain Storm Optimization","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4294811484","doi":"https://doi.org/10.1109/cec55065.2022.9870309"},"language":"en","primary_location":{"id":"doi:10.1109/cec55065.2022.9870309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec55065.2022.9870309","pdf_url":null,"source":{"id":"https://openalex.org/S4363605353","display_name":"2022 IEEE Congress on Evolutionary Computation (CEC)","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":"2022 IEEE Congress on Evolutionary Computation (CEC)","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/A5021303039","display_name":"Kenjiro Takahashi","orcid":null},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenjiro Takahashi","raw_affiliation_strings":["Graduate School of Advanced Mathematical Sciences Meiji University,Tokyo,Japan","Graduate School of Advanced Mathematical Sciences Meiji University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Mathematical Sciences Meiji University,Tokyo,Japan","institution_ids":["https://openalex.org/I16656306"]},{"raw_affiliation_string":"Graduate School of Advanced Mathematical Sciences Meiji University, Tokyo, Japan","institution_ids":["https://openalex.org/I16656306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022209091","display_name":"Yoshikazu Fukuyama","orcid":"https://orcid.org/0000-0002-6115-1676"},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshikazu Fukuyama","raw_affiliation_strings":["Graduate School of Advanced Mathematical Sciences Meiji University,Tokyo,Japan","Graduate School of Advanced Mathematical Sciences Meiji University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Mathematical Sciences Meiji University,Tokyo,Japan","institution_ids":["https://openalex.org/I16656306"]},{"raw_affiliation_string":"Graduate School of Advanced Mathematical Sciences Meiji University, Tokyo, Japan","institution_ids":["https://openalex.org/I16656306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043570940","display_name":"Shuhei Kawaguchi","orcid":null},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]},{"id":"https://openalex.org/I4210133125","display_name":"Mitsubishi Electric (Japan)","ror":"https://ror.org/033y26782","country_code":"JP","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shuhei Kawaguchi","raw_affiliation_strings":["Corporate R&#x0026;D Headquarters in Mitsubishi Electric Co., Ltd and Meiji University,Kanagawa,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Corporate R&#x0026;D Headquarters in Mitsubishi Electric Co., Ltd and Meiji University,Kanagawa,Japan","institution_ids":["https://openalex.org/I16656306","https://openalex.org/I4210133125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069366843","display_name":"Takaomi Sato","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133125","display_name":"Mitsubishi Electric (Japan)","ror":"https://ror.org/033y26782","country_code":"JP","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takaomi Sato","raw_affiliation_strings":["Corporate R&#x0026;D Headquarters in Mitsubishi Electric Co., Ltd and The University of Tokyo,Kanagawa,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Corporate R&#x0026;D Headquarters in Mitsubishi Electric Co., Ltd and The University of Tokyo,Kanagawa,Japan","institution_ids":["https://openalex.org/I4210133125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0717,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86827318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","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/T10551","display_name":"Scheduling and Optimization Algorithms","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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9958999752998352,"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/T12176","display_name":"Optimization and Packing Problems","score":0.9958999752998352,"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/wilcoxon-signed-rank-test","display_name":"Wilcoxon signed-rank test","score":0.6646959185600281},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6245129108428955},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5649213790893555},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5151025652885437},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.511328399181366},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.50592440366745},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.47768861055374146},{"id":"https://openalex.org/keywords/bonferroni-correction","display_name":"Bonferroni correction","score":0.4595573842525482},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.3862159848213196},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3248567283153534},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17338153719902039},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07552975416183472}],"concepts":[{"id":"https://openalex.org/C206041023","wikidata":"https://www.wikidata.org/wiki/Q1751970","display_name":"Wilcoxon signed-rank test","level":3,"score":0.6646959185600281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6245129108428955},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5649213790893555},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5151025652885437},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.511328399181366},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.50592440366745},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.47768861055374146},{"id":"https://openalex.org/C127808970","wikidata":"https://www.wikidata.org/wiki/Q385989","display_name":"Bonferroni correction","level":2,"score":0.4595573842525482},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.3862159848213196},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3248567283153534},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17338153719902039},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07552975416183472},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C12868164","wikidata":"https://www.wikidata.org/wiki/Q1424533","display_name":"Mann\u2013Whitney U test","level":2,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/cec55065.2022.9870309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec55065.2022.9870309","pdf_url":null,"source":{"id":"https://openalex.org/S4363605353","display_name":"2022 IEEE Congress on Evolutionary Computation (CEC)","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":"2022 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5199999809265137,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2088160862","https://openalex.org/W2100131857","https://openalex.org/W2272065637","https://openalex.org/W2560803908","https://openalex.org/W2612447878","https://openalex.org/W2647153655","https://openalex.org/W2732547613","https://openalex.org/W2907797058","https://openalex.org/W3005728138","https://openalex.org/W3189933759"],"related_works":["https://openalex.org/W2390064908","https://openalex.org/W2917228042","https://openalex.org/W2564440352","https://openalex.org/W4253992846","https://openalex.org/W1965088310","https://openalex.org/W2901814704","https://openalex.org/W2461483947","https://openalex.org/W2239990209","https://openalex.org/W2026314750","https://openalex.org/W3204654320"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3],"optimal":[4,39,61],"production":[5,10,40,47,62,66,72,89,122,183],"scheduling":[6,41,63,184],"method":[7,76,95,117,148,207],"using":[8],"the":[9,59,79,87,93,101,113,136,144,154,162,177,181,192,197,210,214,223,227],"simulator":[11],"and":[12,25,65,81,105,139,143,161,187,217],"multi-population":[13],"global-best":[14],"modified":[15],"brain":[16],"storm":[17],"optimization":[18],"(MP-GMBSO).":[19],"Currently,":[20],"in":[21,46],"industry":[22],"sector,":[23],"decarbonization":[24],"carbon":[26],"neutrality":[27],"are":[28,44,96],"approached":[29],"by":[30,153],"technical":[31],"innovations":[32],"such":[33],"as":[34,157,170],"Industry":[35],"4.0.":[36],"In":[37,124,175],"particular,":[38],"researches":[42,64],"which":[43],"important":[45],"environments":[48],"have":[49],"been":[50],"conducted":[51],"actively.":[52],"However,":[53],"there":[54,130],"is":[55,110,127,131,189,194],"a":[56,132,158,171],"gap":[57,80],"between":[58],"previous":[60],"schedule":[67],"generating":[68],"methods":[69,220],"of":[70,92,100,180,196,226],"practical":[71,88],"environments.":[73,90],"The":[74,203],"proposed":[75,94,114,145,204],"can":[77,83,118,208],"fill":[78],"it":[82,126,188],"be":[84,201],"applied":[85],"to":[86,200],"Results":[91],"compared":[97],"with":[98,149,167,222],"those":[99],"conventional":[102,137,215],"MBSO":[103,138,216],"[7]":[104],"GMBSO":[106,140,218],"based":[107,116,141,147,206,219],"methods.":[108],"It":[109],"verified":[111,128],"that":[112,129,191],"MP-GMBSO":[115,146,205],"find":[119],"higher":[120],"quality":[121],"schedules.":[123],"addition,":[125,176],"significant":[133,151],"difference":[134],"among":[135],"methods,":[142],"0.05":[150],"level":[152],"Friedman":[155],"test":[156,160,166],"priori":[159],"Wilcoxon":[163],"signed":[164],"rank":[165],"Bonferroni-Holm":[168],"correction":[169],"post":[172],"hoc":[173],"test.":[174],"objective":[178],"function":[179],"target":[182],"has":[185],"needles":[186],"found":[190],"problem":[193,211],"one":[195],"challenging":[198,224],"problems":[199],"optimized.":[202],"solve":[209],"better":[212],"than":[213],"even":[221],"characteristic":[225],"problem.":[228]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
