{"id":"https://openalex.org/W7117459589","doi":"https://doi.org/10.3390/bdcc10010009","title":"A Monte Carlo Tree Search with Reinforcement Learning and Graph Relational Attention Network for Dynamic Flexible Job Shop Scheduling Problem","display_name":"A Monte Carlo Tree Search with Reinforcement Learning and Graph Relational Attention Network for Dynamic Flexible Job Shop Scheduling Problem","publication_year":2025,"publication_date":"2025-12-26","ids":{"openalex":"https://openalex.org/W7117459589","doi":"https://doi.org/10.3390/bdcc10010009"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc10010009","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10010009","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/bdcc10010009","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yu Jia","orcid":"https://orcid.org/0009-0004-8266-8772"},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Jia","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730050, China"],"raw_orcid":"https://orcid.org/0009-0004-8266-8772","affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730050, China","institution_ids":["https://openalex.org/I22716506"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rui Yang","orcid":"https://orcid.org/0009-0006-9969-113X"},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yang","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730050, China"],"raw_orcid":"https://orcid.org/0009-0006-9969-113X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730050, China","institution_ids":["https://openalex.org/I22716506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121464651","display_name":"Qiuyu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiuyu Zhang","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730050, China"],"raw_orcid":"https://orcid.org/0000-0003-1488-388X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730050, China","institution_ids":["https://openalex.org/I22716506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5121464651"],"corresponding_institution_ids":["https://openalex.org/I22716506"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61245101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"1","first_page":"9","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.7229999899864197,"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":0.7229999899864197,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.02930000051856041,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.017899999395012856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.7401999831199646},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6208999752998352},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5667999982833862},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5446000099182129},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.5134999752044678},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46959999203681946},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.36640000343322754},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.33239999413490295}],"concepts":[{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.7401999831199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722100019454956},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6208999752998352},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5667999982833862},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5446000099182129},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.5134999752044678},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46959999203681946},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45249998569488525},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.36640000343322754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3549000024795532},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C107568181","wikidata":"https://www.wikidata.org/wiki/Q5319000","display_name":"Dynamic priority scheduling","level":3,"score":0.3158000111579895},{"id":"https://openalex.org/C2777243215","wikidata":"https://www.wikidata.org/wiki/Q1493226","display_name":"Job shop","level":5,"score":0.30970001220703125},{"id":"https://openalex.org/C2776435737","wikidata":"https://www.wikidata.org/wiki/Q7915703","display_name":"Variable neighborhood search","level":3,"score":0.30820000171661377},{"id":"https://openalex.org/C158336966","wikidata":"https://www.wikidata.org/wiki/Q3074426","display_name":"Flow shop scheduling","level":4,"score":0.29919999837875366},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C15482360","wikidata":"https://www.wikidata.org/wiki/Q15238499","display_name":"Monte Carlo algorithm","level":3,"score":0.2628999948501587},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.2628999948501587},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26269999146461487},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25999999046325684}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/bdcc10010009","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10010009","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:754e9508bc5e43539f78154ac61b9917","is_oa":true,"landing_page_url":"https://doaj.org/article/754e9508bc5e43539f78154ac61b9917","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing, Vol 10, Iss 1, p 9 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/bdcc10010009","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10010009","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.657295823097229,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G7046736449","display_name":"\u4e91\u5b58\u50a8\u73af\u5883\u4e0b\u57fa\u4e8e\u5185\u5bb9\u7684\u6d77\u91cf\u5bc6\u6587\u8bed\u97f3\u68c0\u7d22\u6280\u672f\u7814\u7a76","funder_award_id":"61862041","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8321427893","display_name":null,"funder_award_id":"21JR7RA120","funder_id":"https://openalex.org/F4320322880","funder_display_name":"Natural Science Foundation of Gansu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322880","display_name":"Natural Science Foundation of Gansu Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,33,67],"dynamic":[1],"flexible":[2],"job":[3],"shop":[4],"scheduling":[5,118],"problem":[6],"(DFJSP)":[7],"with":[8,40,56,69],"machine":[9,27,57],"faults,":[10,58],"considering":[11,59],"the":[12,23,44,54,60,70,81,90,111,117,122,133,142,145,148,158,169],"recovery":[13,61],"condition":[14,62],"and":[15,43,63,106,131,147],"variable":[16,64],"processing":[17,65],"time,":[18],"is":[19,50,86,113,160],"studied":[20],"to":[21,52,88,115,127],"determine":[22],"rescheduling":[24],"scheme":[25],"when":[26,166],"faults":[28],"occur":[29],"in":[30,95,110],"real":[31,96],"time.":[32,66,97],"Monte":[34,82,123],"Carlo":[35,83,124],"Tree":[36],"Search":[37],"(MCTS)":[38],"algorithm":[39],"reinforcement":[41],"learning":[42],"relational-enhanced":[45,105],"graph":[46,100,108],"attention":[47,101],"network":[48,102,109],"(MGRL)":[49],"presented":[51],"address":[53],"DFJSP":[55],"MCTS":[68,94,136],"skip-node":[71,149],"restart":[72,150],"strategy,":[73],"which":[74],"utilizes":[75],"local":[76],"optimal":[77,161],"solutions":[78],"found":[79],"during":[80],"sampling":[84,125,129],"process,":[85],"designed":[87,114],"enhance":[89,132],"optimization":[91,137],"efficiency":[92],"of":[93,135,144],"A":[98],"relational":[99],"(RGAT),":[103],"a":[104],"transformer-integrated":[107],"MGRL,":[112],"analyze":[116],"disjunctive":[119],"graph,":[120],"guide":[121],"method":[126],"improve":[128],"efficiency,":[130],"quality":[134],"decisions.":[138],"Experimental":[139],"results":[140,155],"demonstrate":[141],"effectiveness":[143],"RGAT":[146],"strategy.":[151],"Further":[152],"application":[153],"analysis":[154],"show":[156],"that":[157],"MGRL":[159],"among":[162],"all":[163],"comparison":[164],"methods":[165],"algorithms":[167],"solve":[168],"DFJSP.":[170]},"counts_by_year":[],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-12-29T00:00:00"}
