{"id":"https://openalex.org/W4205825338","doi":"https://doi.org/10.1109/tase.2021.3129439","title":"Learning-Based Grey Wolf Optimizer for Stochastic Flexible Job Shop Scheduling","display_name":"Learning-Based Grey Wolf Optimizer for Stochastic Flexible Job Shop Scheduling","publication_year":2022,"publication_date":"2022-01-17","ids":{"openalex":"https://openalex.org/W4205825338","doi":"https://doi.org/10.1109/tase.2021.3129439"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2021.3129439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2021.3129439","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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/A5043725403","display_name":"ChengRan Lin","orcid":"https://orcid.org/0000-0001-9924-4408"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"ChengRan Lin","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079155612","display_name":"Zhengcai Cao","orcid":"https://orcid.org/0000-0003-0344-0207"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ZhengCai Cao","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081318069","display_name":"MengChu Zhou","orcid":"https://orcid.org/0000-0002-5408-8752"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]},{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]}],"countries":["MO","US"],"is_corresponding":false,"raw_author_name":"MengChu Zhou","raw_affiliation_strings":["Institute of Systems Engineering and the Collaborative Laboratory for Intelligent Science and Systems, Macau University of Science and Technology, Macao, China","Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Institute of Systems Engineering and the Collaborative Laboratory for Intelligent Science and Systems, Macau University of Science and Technology, Macao, China","institution_ids":["https://openalex.org/I111950717"]},{"raw_affiliation_string":"Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043725403"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":10.824,"has_fulltext":false,"cited_by_count":85,"citation_normalized_percentile":{"value":0.98632977,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"19","issue":"4","first_page":"3659","last_page":"3671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9998999834060669,"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":0.9998999834060669,"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/T12288","display_name":"Optimization and Search Problems","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9890000224113464,"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":0.7348071336746216},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6380233764648438},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5809699296951294},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.5565707087516785},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.544490396976471},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.46809864044189453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22169804573059082},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09743332862854004}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348071336746216},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6380233764648438},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5809699296951294},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.5565707087516785},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.544490396976471},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.46809864044189453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22169804573059082},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09743332862854004},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2021.3129439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2021.3129439","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G36332496","display_name":null,"funder_award_id":"52175002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4369383357","display_name":null,"funder_award_id":"0047/2021/A1","funder_id":"https://openalex.org/F4320323893","funder_display_name":"Fundo para o Desenvolvimento das Ci\u00eancias e da Tecnologia"},{"id":"https://openalex.org/G5894778791","display_name":null,"funder_award_id":"PAL-N201804","funder_id":"https://openalex.org/F4320335661","funder_display_name":"State Key Laboratory of Synthetical Automation for Process Industries"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323893","display_name":"Fundo para o Desenvolvimento das Ci\u00eancias e da Tecnologia","ror":"https://ror.org/05vna4324"},{"id":"https://openalex.org/F4320335661","display_name":"State Key Laboratory of Synthetical Automation for Process Industries","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1491412371","https://openalex.org/W1536615069","https://openalex.org/W1545960569","https://openalex.org/W1581014372","https://openalex.org/W1976931273","https://openalex.org/W1996356713","https://openalex.org/W2005216095","https://openalex.org/W2005294352","https://openalex.org/W2007240797","https://openalex.org/W2015294321","https://openalex.org/W2022529231","https://openalex.org/W2025746164","https://openalex.org/W2032952036","https://openalex.org/W2042928785","https://openalex.org/W2056462584","https://openalex.org/W2061438946","https://openalex.org/W2066933614","https://openalex.org/W2068142293","https://openalex.org/W2121863487","https://openalex.org/W2124154451","https://openalex.org/W2174155470","https://openalex.org/W2198739890","https://openalex.org/W2275596639","https://openalex.org/W2327828747","https://openalex.org/W2342596926","https://openalex.org/W2343767601","https://openalex.org/W2344852273","https://openalex.org/W2507510427","https://openalex.org/W2555999855","https://openalex.org/W2565904487","https://openalex.org/W2738540198","https://openalex.org/W2764192835","https://openalex.org/W2768233943","https://openalex.org/W2829536470","https://openalex.org/W2890194976","https://openalex.org/W2892315936","https://openalex.org/W2899007025","https://openalex.org/W2904387011","https://openalex.org/W2906331811","https://openalex.org/W2921561807","https://openalex.org/W2939395981","https://openalex.org/W2951307174","https://openalex.org/W2963864421","https://openalex.org/W2995030975","https://openalex.org/W3028316120","https://openalex.org/W3033703165","https://openalex.org/W3092878571","https://openalex.org/W3115742705","https://openalex.org/W3119363261","https://openalex.org/W3128122525","https://openalex.org/W3167334575","https://openalex.org/W3173929531","https://openalex.org/W3176242461","https://openalex.org/W3201324775","https://openalex.org/W4237029372","https://openalex.org/W6678234102","https://openalex.org/W6684921986","https://openalex.org/W6745873365"],"related_works":["https://openalex.org/W1581479499","https://openalex.org/W2024806294","https://openalex.org/W2095303169","https://openalex.org/W997954202","https://openalex.org/W4236295709","https://openalex.org/W2530969325","https://openalex.org/W2520902986","https://openalex.org/W4309332046","https://openalex.org/W2950969551","https://openalex.org/W1553364762"],"abstract_inverted_index":{"This":[0],"work":[1],"considers":[2],"a":[3,18,37,40,88,98,103,113,118,126,224,240,297,318,328,337],"stochastic":[4,209,225],"flexible":[5],"job":[6],"shop":[7],"scheduling":[8,197,342],"with":[9,102,165,176],"limited":[10],"extra":[11],"resources":[12],"and":[13,33,72,131,152,167,243,250,287,326,330,346,356],"machine-dependent":[14],"setup":[15],"time":[16,339],"in":[17,36,239,258,336],"semiconductor":[19,195,366],"manufacturing":[20,63,196,210,367],"environment,":[21],"which":[22,55],"is":[23,45,56,65,109,216,255,354],"an":[24,49,268],"NP-hard":[25],"problem.":[26],"In":[27,47,314],"order":[28],"to":[29,67,92,111,173,188,193,202,232,301,322,364],"obtain":[30,93],"its":[31,183,324],"reliable":[32],"high-performance":[34],"schedule":[35,332],"reasonable":[38],"time,":[39],"learning-based":[41],"grey":[42,119],"wolf":[43,120],"optimizer":[44],"proposed.":[46],"it,":[48],"optimal":[50,82,147,269,277],"computing":[51,70,83,148,270],"budget":[52,71,84,149,271],"allocation-based":[53,150,272],"approach,":[54],"designed":[57,105],"for":[58,128,274,340],"two":[59,203],"scenarios":[60],"from":[61],"real":[62],"environments,":[64],"proposed":[66,139,159,307,352],"intelligently":[68],"allocate":[69],"improve":[73],"search":[74],"efficiency.":[75],"It":[76],"extends":[77],"the":[78,138,145,153,158,234,263,276,292,303,351],"application":[79],"area":[80],"of":[81,117,137,144,157,246,279,305],"allocation":[85],"by":[86],"laying":[87],"theoretic":[89,142],"foundation.":[90],"Besides,":[91],"proper":[94,253],"control":[95],"parameters":[96,254,304],"iteratively,":[97],"reinforcement":[99,298],"learning":[100,299],"algorithm":[101,160,300],"newly":[104],"delay":[106,319],"update":[107,320],"strategy":[108,321],"used":[110],"build":[112],"parameter":[114],"tuning":[115],"scheme":[116,123],"optimizer.":[121],"The":[122,141,180],"acts":[124],"as":[125],"guide":[127],"balancing":[129],"global":[130],"local":[132],"search,":[133],"thereby":[134],"enhancing":[135],"effectiveness":[136],"algorithm.":[140],"interpretation":[143],"developed":[146],"approach":[151],"convergence":[154],"analysis":[155],"results":[156,181,348],"are":[161,171,190,248],"presented.":[162],"Various":[163],"experiments":[164],"benchmarks":[166],"randomly":[168],"generated":[169],"cases":[170],"performed":[172],"compare":[174],"it":[175,359],"several":[177],"updated":[178],"algorithms.":[179],"shows":[182],"superiority":[184],"over":[185],"them.":[186],"Note":[187],"Practitioners\u2014Meta-heuristic":[189],"often":[191],"deployed":[192],"solve":[194],"problems.":[198,343],"However,":[199],"they":[200,207],"face":[201,208],"thorny":[204],"issues":[205],"when":[206],"environments.":[211,260],"1)":[212],"their":[213,252],"computational":[214],"efficiency":[215],"quite":[217],"low,":[218],"thus":[219],"requiring":[220],"substantial":[221],"improvement,":[222],"since":[223],"optimization":[226],"problem":[227],"requires":[228],"Monte":[229],"Carlo":[230],"sampling":[231,280],"estimate":[233],"actual":[235],"objective":[236],"function":[237],"values":[238],"precise":[241],"manner;":[242],"2)":[244],"most":[245],"them":[247],"parameter-sensitive,":[249],"choosing":[251],"highly":[256],"challenging":[257],"such":[259],"To":[261,290],"address":[262,291],"first":[264],"issue,":[265],"we":[266,295,316],"develop":[267],"method":[273,308,353],"deciding":[275],"numbers":[278],"times":[281],"based":[282],"on":[283],"both":[284],"prior":[285],"knowledge":[286],"simulation":[288],"results.":[289],"second":[293],"one,":[294],"propose":[296],"self-adjust":[302],"our":[306],"called":[309],"Learning-based":[310],"Grey":[311],"Wolf":[312],"Optimizer.":[313],"addition,":[315],"design":[317],"enhance":[323],"robustness,":[325],"thus,":[327],"feasible":[329],"high-quality":[331],"can":[333,360],"be":[334,361],"founded":[335],"short":[338],"real-time":[341],"Theoretic":[344],"proofs":[345],"experimental":[347],"show":[349],"that":[350],"effective":[355],"efficient.":[357],"Consequently,":[358],"readily":[362],"applicable":[363],"practical":[365],"systems.":[368]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":32},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":9}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
