{"id":"https://openalex.org/W4398758462","doi":"https://doi.org/10.1145/3652628.3652670","title":"Multi-Constraint Flexible Job Scheduling Algorithm Based on DDQN: A Deep Reinforcement Learning Algorithm for Solving Practical Job Scheduling Problems","display_name":"Multi-Constraint Flexible Job Scheduling Algorithm Based on DDQN: A Deep Reinforcement Learning Algorithm for Solving Practical Job Scheduling Problems","publication_year":2023,"publication_date":"2023-11-17","ids":{"openalex":"https://openalex.org/W4398758462","doi":"https://doi.org/10.1145/3652628.3652670"},"language":"en","primary_location":{"id":"doi:10.1145/3652628.3652670","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3652628.3652670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Artificial Intelligence and Computer Engineering","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/A5102972553","display_name":"Lin Liu","orcid":"https://orcid.org/0009-0004-1894-5181"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["Hangzhou Zhiyuan Research Institute Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0004-1894-5181","affiliations":[{"raw_affiliation_string":"Hangzhou Zhiyuan Research Institute Co., Ltd., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053124601","display_name":"Zijing Liang","orcid":"https://orcid.org/0009-0000-7311-6563"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zijing Liang","raw_affiliation_strings":["Hangzhou Zhiyuan Research Institute Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0000-7311-6563","affiliations":[{"raw_affiliation_string":"Hangzhou Zhiyuan Research Institute Co., Ltd., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014883198","display_name":"Yifan Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifan Hong","raw_affiliation_strings":["Hangzhou Zhiyuan Research Institute Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0000-7274-0436","affiliations":[{"raw_affiliation_string":"Hangzhou Zhiyuan Research Institute Co., Ltd., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044031472","display_name":"Ke Liu","orcid":"https://orcid.org/0009-0003-0165-6423"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke Liu","raw_affiliation_strings":["Hangzhou Zhiyuan Research Institute Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0003-0165-6423","affiliations":[{"raw_affiliation_string":"Hangzhou Zhiyuan Research Institute Co., Ltd., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040677980","display_name":"H J Wang","orcid":"https://orcid.org/0009-0001-2628-7092"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Wang","raw_affiliation_strings":["Hangzhou Zhiyuan Research Institute Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0001-2628-7092","affiliations":[{"raw_affiliation_string":"Hangzhou Zhiyuan Research Institute Co., Ltd., China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001005576","display_name":"Penghui Shang","orcid":"https://orcid.org/0009-0001-8431-4247"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Penghui Shang","raw_affiliation_strings":["Hangzhou Zhiyuan Research Institute Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0001-8431-4247","affiliations":[{"raw_affiliation_string":"Hangzhou Zhiyuan Research Institute Co., Ltd., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"248","last_page":"256"},"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9951000213623047,"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":0.9833999872207642,"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":0.7584101557731628},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6859385371208191},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5736653208732605},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5168874263763428},{"id":"https://openalex.org/keywords/dynamic-priority-scheduling","display_name":"Dynamic priority scheduling","score":0.5126098990440369},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.49954676628112793},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4803082346916199},{"id":"https://openalex.org/keywords/flow-shop-scheduling","display_name":"Flow shop scheduling","score":0.47757747769355774},{"id":"https://openalex.org/keywords/fair-share-scheduling","display_name":"Fair-share scheduling","score":0.45450007915496826},{"id":"https://openalex.org/keywords/rate-monotonic-scheduling","display_name":"Rate-monotonic scheduling","score":0.4429692029953003},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34368908405303955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2802569270133972},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.2451183795928955},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.23996314406394958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7584101557731628},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6859385371208191},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5736653208732605},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5168874263763428},{"id":"https://openalex.org/C107568181","wikidata":"https://www.wikidata.org/wiki/Q5319000","display_name":"Dynamic priority scheduling","level":3,"score":0.5126098990440369},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.49954676628112793},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4803082346916199},{"id":"https://openalex.org/C158336966","wikidata":"https://www.wikidata.org/wiki/Q3074426","display_name":"Flow shop scheduling","level":4,"score":0.47757747769355774},{"id":"https://openalex.org/C31689143","wikidata":"https://www.wikidata.org/wiki/Q733809","display_name":"Fair-share scheduling","level":3,"score":0.45450007915496826},{"id":"https://openalex.org/C127456818","wikidata":"https://www.wikidata.org/wiki/Q238879","display_name":"Rate-monotonic scheduling","level":4,"score":0.4429692029953003},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34368908405303955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2802569270133972},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.2451183795928955},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.23996314406394958},{"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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3652628.3652670","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3652628.3652670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Artificial Intelligence and Computer Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W615470768","https://openalex.org/W2007255274","https://openalex.org/W2045321449","https://openalex.org/W2094464773","https://openalex.org/W2163465352","https://openalex.org/W2170006013","https://openalex.org/W2599499292","https://openalex.org/W3092208345","https://openalex.org/W3134664017","https://openalex.org/W3159896318","https://openalex.org/W4242399344","https://openalex.org/W4255870372"],"related_works":["https://openalex.org/W2184166483","https://openalex.org/W2397293317","https://openalex.org/W2377713709","https://openalex.org/W2225350526","https://openalex.org/W2949165180","https://openalex.org/W2838819579","https://openalex.org/W131757205","https://openalex.org/W4399221052","https://openalex.org/W2538210412","https://openalex.org/W2384952691"],"abstract_inverted_index":{"As":[0],"an":[1,167],"important":[2,14],"part":[3],"of":[4,9,56,77,190,207,220,229],"intelligent":[5,30,107],"manufacturing,":[6],"reasonable":[7],"scheduling":[8,31,108,149,161],"production":[10,52,85],"planning":[11],"is":[12,80,110,141,182,200,215],"very":[13],"for":[15],"reducing":[16],"costs":[17],"and":[18,39,53,63,98,117,121,158,211,227],"increasing":[19],"efficiency.":[20],"This":[21],"paper":[22,68],"considers":[23],"that":[24,187,206,219],"the":[25,35,40,45,49,83,106,118,126,135,148,171,180,188,191,196,208,212,225,230],"current":[26],"algorithms":[27],"related":[28,178],"to":[29,81,125,151,165,179,205],"do":[32],"not":[33],"consider":[34],"actual":[36,50],"constraints":[37,58],"enough,":[38],"solution":[41,192,213],"efficiency":[42],"cannot":[43],"satisfy":[44],"application":[46],"requirements.":[47],"Considering":[48],"industrial":[51],"a":[54,70,113,153],"variety":[55],"practical":[57],"including":[59,87],"employee":[60,91],"attendance":[61],"time":[62],"machine":[64],"start-up":[65],"time,":[66],"this":[67,78,104,133],"proposes":[69],"deep":[71],"reinforcement":[72,197],"learning":[73,198],"algorithm.":[74,232],"The":[75],"goal":[76,181],"research":[79],"minimize":[82],"total":[84],"cost":[86],"product":[88,100],"processing":[89],"costs,":[90,93,96],"overtime":[92],"order":[94],"back-order":[95],"finished":[97],"semi-finished":[99],"inventory":[101],"costs.":[102],"In":[103,132],"paper,":[105,134],"problem":[109],"modeled":[111],"as":[112],"Markov":[114],"decision-making":[115,130],"process,":[116],"agent":[119],"selects":[120],"executes":[122],"actions":[123],"according":[124],"state":[127],"at":[128],"each":[129],"stage.":[131],"Double":[136],"DQN":[137],"neural":[138],"network":[139],"architecture":[140],"built.":[142],"Seven":[143],"features":[144],"are":[145,163],"extracted":[146],"from":[147],"environment":[150],"form":[152,166],"feature":[154],"vector":[155],"representation":[156],"state,":[157],"six":[159],"composite":[160],"rules":[162],"designed":[164],"action":[168],"set":[169,193],"considering":[170],"optimization":[172],"goal.":[173],"A":[174],"reward":[175],"function":[176],"closely":[177],"designed.":[183],"Numerical":[184],"experiments":[185],"show":[186],"quality":[189],"obtained":[194],"by":[195],"algorithm":[199],"better":[201,217],"than":[202,218],"or":[203],"similar":[204],"genetic":[209],"algorithm,":[210],"speed":[214],"significantly":[216],"other":[221],"algorithms,":[222],"which":[223],"proves":[224],"effectiveness":[226],"feasibility":[228],"proposed":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}