{"id":"https://openalex.org/W3166794154","doi":"https://doi.org/10.1145/3447548.3467135","title":"A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem","display_name":"A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3166794154","doi":"https://doi.org/10.1145/3447548.3467135","mag":"3166794154"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467135","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467135","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","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/A5101480779","display_name":"Fei Ni","orcid":"https://orcid.org/0000-0003-0734-6744"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Ni","raw_affiliation_strings":["Huazhong Unviersity of Science and Technology, Wuhan, AE, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong Unviersity of Science and Technology, Wuhan, AE, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047509839","display_name":"Jianye Hao","orcid":"https://orcid.org/0000-0002-0422-8235"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianye Hao","raw_affiliation_strings":["Tianjin University & Huawei Noah's Ark Lab, Tianjin, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University & Huawei Noah's Ark Lab, Tianjin, AA, China","institution_ids":["https://openalex.org/I162868743","https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039684298","display_name":"Jiawen Lu","orcid":"https://orcid.org/0000-0002-1059-4522"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawen Lu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, AA, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049905353","display_name":"Xialiang Tong","orcid":"https://orcid.org/0009-0006-8153-1576"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xialiang Tong","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, AA, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078949174","display_name":"Mingxuan Yuan","orcid":"https://orcid.org/0000-0002-2236-8784"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxuan Yuan","raw_affiliation_strings":["Huawei Noah's Ark Lab, Hong Kong, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Hong Kong, AA, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024158764","display_name":"Jiahui Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Duan","raw_affiliation_strings":["Sichuan University, Chengdu, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University, Chengdu, AA, China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029760958","display_name":"Yi Ma","orcid":"https://orcid.org/0000-0002-0615-1091"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Ma","raw_affiliation_strings":["Tianjin University, Tianjin, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, AA, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033526822","display_name":"Kun He","orcid":"https://orcid.org/0000-0001-7627-4604"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun He","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, AA, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, AA, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.7899,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.995352,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3441","last_page":"3451"},"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":0.9954000115394592,"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/T12782","display_name":"Assembly Line Balancing Optimization","score":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.85936439037323},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7273913025856018},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5033294558525085},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4857352375984192},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.4733988046646118},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.4598693549633026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3388635814189911},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.323422908782959},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.29129064083099365},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.254763662815094},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.1462600827217102}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.85936439037323},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7273913025856018},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5033294558525085},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4857352375984192},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.4733988046646118},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4598693549633026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3388635814189911},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.323422908782959},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.29129064083099365},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.254763662815094},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.1462600827217102},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467135","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467135","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1949153500","https://openalex.org/W1997058568","https://openalex.org/W2004436626","https://openalex.org/W2006751452","https://openalex.org/W2046283054","https://openalex.org/W2059420512","https://openalex.org/W2060880823","https://openalex.org/W2073601282","https://openalex.org/W2079033567","https://openalex.org/W2090069860","https://openalex.org/W2625622743","https://openalex.org/W2760631911","https://openalex.org/W2932097000","https://openalex.org/W2963403868","https://openalex.org/W2964926209","https://openalex.org/W2968986602","https://openalex.org/W2999708372","https://openalex.org/W3009389630","https://openalex.org/W3034384938","https://openalex.org/W3094181369"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3204654320","https://openalex.org/W3015684221"],"abstract_inverted_index":{"Hybrid":[0],"Flow":[1],"Shop":[2],"Scheduling":[3],"Problem":[4],"(HFSP)":[5],"is":[6,130,191],"an":[7],"essential":[8],"problem":[9],"in":[10],"the":[11,18,23,29,50,58,66,69,73,101,107,113,124,134,143,149,153,156,173,202,217],"automated":[12],"warehouse":[13],"scheduling,":[14],"aiming":[15],"at":[16],"optimizing":[17],"sequence":[19],"of":[20,25,57,68,132,152,182,219],"jobs":[21],"and":[22,54,105,123,141,164,175,206],"assignment":[24],"machines":[26],"to":[27,44,64,98,111,138,171,193],"utilize":[28],"makespan":[30],"or":[31],"other":[32],"objectives.":[33],"Existing":[34],"algorithms":[35],"adopt":[36],"fixed":[37],"search":[38,117,121,135,144],"paradigm":[39,136],"based":[40,94,127],"on":[41,200],"expert":[42],"knowledge":[43],"seek":[45],"satisfactory":[46],"solutions.":[47],"However,":[48],"considering":[49],"varying":[51],"data":[52,80],"distribution":[53],"large":[55],"scale":[56],"practical":[59,102],"HFSP,":[60],"these":[61],"methods":[62],"fail":[63],"guarantee":[65],"quality":[67],"obtained":[70],"solution":[71],"under":[72],"real-time":[74],"requirement,":[75],"especially":[76],"facing":[77],"extremely":[78],"different":[79],"distribution.":[81],"To":[82],"address":[83],"this":[84],"challenge,":[85],"we":[86,147],"propose":[87],"a":[88,186],"novel":[89],"Multi-Graph":[90],"Attributed":[91],"Reinforcement":[92],"Learning":[93],"Optimization":[95],"(MGRO)":[96],"algorithm":[97],"better":[99],"tackle":[100],"large-scale":[103],"HFSP":[104],"improve":[106],"existing":[108,222],"algorithm.":[109],"Owing":[110],"incorporating":[112],"reinforcement":[114],"learning-based":[115],"policy":[116],"approach":[118,190],"with":[119],"classic":[120],"operators":[122],"powerful":[125],"multi-graph":[126],"representation,":[128],"MGRO":[129,177,220],"capable":[131],"adjusting":[133],"according":[137],"specific":[139],"instances":[140],"enhancing":[142],"efficiency.":[145],"Specifically,":[146],"formulate":[148],"Gantt":[150],"chart":[151],"instance":[154],"into":[155],"multi-graph-structured":[157],"data.":[158],"Then":[159],"Graph":[160],"Neural":[161],"Network":[162],"(GNN)":[163],"attention-based":[165],"adaptive":[166],"weighted":[167],"pooling":[168],"are":[169],"employed":[170],"represent":[172],"state":[174],"make":[176],"size-agnostic":[178],"across":[179],"arbitrary":[180],"sizes":[181],"instances.":[183],"In":[184],"addition,":[185],"useful":[187],"reward":[188],"shaping":[189],"designed":[192],"facilitate":[194],"model":[195],"convergence.":[196],"Extensive":[197],"numerical":[198],"experiments":[199],"both":[201],"publicly":[203],"available":[204],"dataset":[205,209],"real":[207],"industrial":[208],"from":[210],"Huawei":[211],"Supply":[212],"Chain":[213],"Business":[214],"Unit":[215],"demonstrate":[216],"superiority":[218],"over":[221],"baselines.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}