{"id":"https://openalex.org/W2931544713","doi":"https://doi.org/10.1080/00207543.2019.1597291","title":"A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling","display_name":"A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling","publication_year":2019,"publication_date":"2019-03-30","ids":{"openalex":"https://openalex.org/W2931544713","doi":"https://doi.org/10.1080/00207543.2019.1597291","mag":"2931544713"},"language":"en","primary_location":{"id":"doi:10.1080/00207543.2019.1597291","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2019.1597291","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Production Research","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/A5081960668","display_name":"Zhi Pei","orcid":"https://orcid.org/0000-0001-6808-1490"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhi Pei","raw_affiliation_strings":["Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People\u2019s Republic of China","Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0001-6808-1490","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People\u2019s Republic of China","institution_ids":["https://openalex.org/I55712492"]},{"raw_affiliation_string":"Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043677526","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0002-7590-3752"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefang Zhang","raw_affiliation_strings":["Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People\u2019s Republic of China","Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People\u2019s Republic of China","institution_ids":["https://openalex.org/I55712492"]},{"raw_affiliation_string":"Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423655","display_name":"Li Zheng","orcid":"https://orcid.org/0000-0001-7313-573X"},"institutions":[{"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":"Li Zheng","raw_affiliation_strings":["Department of Industrial Engineering, Tsinghua University, Beijing 100084, People\u2019s Republic of China","Department of Industrial Engineering, Tsinghua University, Beijing 100084, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing 100084, People\u2019s Republic of China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing 100084, People's Republic of China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112563802","display_name":"Mingzhong Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhong Wan","raw_affiliation_strings":["Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People\u2019s Republic of China","Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People\u2019s Republic of China","institution_ids":["https://openalex.org/I55712492"]},{"raw_affiliation_string":"Department of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, People's Republic of China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081960668"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":null,"apc_paid":null,"fwci":3.4122,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.93205258,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"58","issue":"2","first_page":"487","last_page":"508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":1.0,"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":1.0,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9977999925613403,"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/T12176","display_name":"Optimization and Packing Problems","score":0.9939000010490417,"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/job-shop-scheduling","display_name":"Job shop scheduling","score":0.8396764993667603},{"id":"https://openalex.org/keywords/column-generation","display_name":"Column generation","score":0.675259530544281},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6636285185813904},{"id":"https://openalex.org/keywords/job-shop","display_name":"Job shop","score":0.5749868154525757},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.564902663230896},{"id":"https://openalex.org/keywords/integer-programming","display_name":"Integer programming","score":0.5548718571662903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5402593016624451},{"id":"https://openalex.org/keywords/flow-shop-scheduling","display_name":"Flow shop scheduling","score":0.5060581564903259},{"id":"https://openalex.org/keywords/open-shop-scheduling","display_name":"Open-shop scheduling","score":0.4836893677711487},{"id":"https://openalex.org/keywords/rate-monotonic-scheduling","display_name":"Rate-monotonic scheduling","score":0.43139445781707764},{"id":"https://openalex.org/keywords/dynamic-priority-scheduling","display_name":"Dynamic priority scheduling","score":0.39704790711402893},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32471412420272827},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.1216924786567688}],"concepts":[{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.8396764993667603},{"id":"https://openalex.org/C168956720","wikidata":"https://www.wikidata.org/wiki/Q3123181","display_name":"Column generation","level":2,"score":0.675259530544281},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6636285185813904},{"id":"https://openalex.org/C2777243215","wikidata":"https://www.wikidata.org/wiki/Q1493226","display_name":"Job shop","level":5,"score":0.5749868154525757},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.564902663230896},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.5548718571662903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5402593016624451},{"id":"https://openalex.org/C158336966","wikidata":"https://www.wikidata.org/wiki/Q3074426","display_name":"Flow shop scheduling","level":4,"score":0.5060581564903259},{"id":"https://openalex.org/C35799125","wikidata":"https://www.wikidata.org/wiki/Q7095711","display_name":"Open-shop scheduling","level":5,"score":0.4836893677711487},{"id":"https://openalex.org/C127456818","wikidata":"https://www.wikidata.org/wiki/Q238879","display_name":"Rate-monotonic scheduling","level":4,"score":0.43139445781707764},{"id":"https://openalex.org/C107568181","wikidata":"https://www.wikidata.org/wiki/Q5319000","display_name":"Dynamic priority scheduling","level":3,"score":0.39704790711402893},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32471412420272827},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.1216924786567688},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00207543.2019.1597291","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2019.1597291","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Production Research","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:taf:tprsxx:v:58:y:2020:i:2:p:487-508","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/00207543.2019.1597291","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G3033548306","display_name":null,"funder_award_id":"LY18G010017","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G3594911729","display_name":null,"funder_award_id":"51305400","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4255926405","display_name":null,"funder_award_id":"LQ12G01008","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G978423042","display_name":"\u5171\u4eab\u7ecf\u6d4e\u6a21\u5f0f\u4e0b\u8003\u8651\u4f9b\u9700\u53cc\u65b9\u884c\u4e3a\u7279\u5f81\u7684\u5206\u5e03\u5f0f\u5236\u9020\u7cfb\u7edf\u51b3\u7b56\u673a\u7406\u7814\u7a76","funder_award_id":"71871203","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"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1488422606","https://openalex.org/W1618936918","https://openalex.org/W1828885239","https://openalex.org/W1964580560","https://openalex.org/W1967179727","https://openalex.org/W1973696055","https://openalex.org/W1984200231","https://openalex.org/W1994534839","https://openalex.org/W1995620551","https://openalex.org/W2011039300","https://openalex.org/W2023581023","https://openalex.org/W2024672654","https://openalex.org/W2024793042","https://openalex.org/W2044667276","https://openalex.org/W2068265913","https://openalex.org/W2071354142","https://openalex.org/W2083825352","https://openalex.org/W2112849942","https://openalex.org/W2120350145","https://openalex.org/W2122967269","https://openalex.org/W2124714712","https://openalex.org/W2124872196","https://openalex.org/W2135986386","https://openalex.org/W2136458005","https://openalex.org/W2144946856","https://openalex.org/W2167580124","https://openalex.org/W2170716909","https://openalex.org/W2204206022","https://openalex.org/W2230700996","https://openalex.org/W2235122508","https://openalex.org/W2287256299","https://openalex.org/W2321948413","https://openalex.org/W2343121647","https://openalex.org/W2360575242","https://openalex.org/W2407506046","https://openalex.org/W2470126219","https://openalex.org/W2554975820","https://openalex.org/W2561944365","https://openalex.org/W2747561859","https://openalex.org/W2750312811","https://openalex.org/W2761608996","https://openalex.org/W2768048291","https://openalex.org/W2791306173","https://openalex.org/W2805905065","https://openalex.org/W3151157462","https://openalex.org/W4231610975"],"related_works":["https://openalex.org/W2025157869","https://openalex.org/W2074650926","https://openalex.org/W2087693503","https://openalex.org/W2031676021","https://openalex.org/W82886544","https://openalex.org/W2155809154","https://openalex.org/W2070373866","https://openalex.org/W2012754152","https://openalex.org/W2949165180","https://openalex.org/W2353206602"],"abstract_inverted_index":{"Job":[0],"shop":[1,30,41,80],"scheduling,":[2],"as":[3],"one":[4],"of":[5,128],"the":[6,37,65,136,141,155],"classical":[7],"scheduling":[8,31,42,81],"problems,":[9],"has":[10,55],"been":[11],"widely":[12],"studied":[13],"in":[14,49,164],"literatures,":[15],"and":[16,86,98,122],"proved":[17],"to":[18,27,35,43],"be":[19,47],"mostly":[20],"NP-hard.":[21],"Although":[22],"it":[23],"is":[24,70,90,111,120],"extremely":[25],"difficult":[26],"solve":[28,103,150],"job":[29,40,54,62,79],"with":[32,83],"no-wait":[33,39,78],"constraint":[34],"optimality,":[36],"two-machine":[38],"minimise":[44],"makespan":[45],"could":[46],"solvable":[48],"polynomial":[50],"time":[51],"when":[52],"each":[53],"exactly":[56],"two":[57],"equal":[58],"length":[59],"operations":[60],"(proportionate":[61],"shop).":[63],"In":[64,113],"present":[66],"paper,":[67],"an":[68],"extension":[69],"attempted":[71],"by":[72,124,146],"considering":[73],"a":[74,87,95,99,106,115],"proportionate":[75],"flexible":[76],"two-stage":[77],"problem":[82,97],"minimum":[84],"makespan,":[85],"set-covering":[88],"formulation":[89],"put":[91],"forward":[92],"which":[93],"contains":[94],"master":[96],"pricing":[100],"problem.":[101],"To":[102],"this":[104],"problem,":[105],"column":[107],"generation":[108],"(CG)-based":[109],"approach":[110],"implemented.":[112],"comparison,":[114],"mixed":[116,142],"integer":[117,143],"programming":[118],"model":[119,144],"constructed":[121],"optimised":[123],"Cplex.":[125],"A":[126],"series":[127],"randomly":[129],"generated":[130],"numerical":[131],"instances":[132],"are":[133],"calculated.":[134],"And":[135],"testing":[137],"result":[138],"shows":[139],"that":[140],"handled":[145],"Cplex":[147],"can":[148,159],"only":[149],"small":[151],"scale":[152],"cases,":[153],"while":[154],"proposed":[156],"CG-based":[157],"method":[158],"conquer":[160],"larger":[161],"size":[162],"problems":[163],"acceptable":[165],"time.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
