{"id":"https://openalex.org/W4389610202","doi":"https://doi.org/10.1109/tnnls.2023.3338237","title":"An Off-Policy Reinforcement Learning-Based Adaptive Optimization Method for Dynamic Resource Allocation Problem","display_name":"An Off-Policy Reinforcement Learning-Based Adaptive Optimization Method for Dynamic Resource Allocation Problem","publication_year":2023,"publication_date":"2023-12-12","ids":{"openalex":"https://openalex.org/W4389610202","doi":"https://doi.org/10.1109/tnnls.2023.3338237","pmid":"https://pubmed.ncbi.nlm.nih.gov/38090867"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3338237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3338237","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5023239277","display_name":"Baiyang He","orcid":"https://orcid.org/0009-0008-0784-8983"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baiyang He","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101795886","display_name":"Ying Meng","orcid":"https://orcid.org/0000-0002-9504-3745"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Meng","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China","Ministry of Education, National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Ministry of Education, National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080304378","display_name":"Lixin Tang","orcid":"https://orcid.org/0000-0002-9950-5169"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Tang","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023239277"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.8652,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79798503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"36","issue":"2","first_page":"3504","last_page":"3518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9968000054359436,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9905999898910522,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8403977751731873},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7467173337936401},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6468918919563293},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4697342813014984},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4341431260108948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3264119029045105},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12868672609329224},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12444847822189331}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8403977751731873},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7467173337936401},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6468918919563293},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4697342813014984},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4341431260108948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3264119029045105},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12868672609329224},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12444847822189331},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3338237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3338237","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38090867","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38090867","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3596273737","display_name":null,"funder_award_id":"72002028","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3726562248","display_name":null,"funder_award_id":"B16009","funder_id":"https://openalex.org/F4320336033","funder_display_name":"Overseas Expertise Introduction Project for Discipline Innovation"},{"id":"https://openalex.org/G5303336969","display_name":null,"funder_award_id":"72192830","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G852931893","display_name":null,"funder_award_id":"72192831","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/F4320336033","display_name":"Overseas Expertise Introduction Project for Discipline Innovation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W127063582","https://openalex.org/W1577359755","https://openalex.org/W1726070994","https://openalex.org/W1966290355","https://openalex.org/W1992527911","https://openalex.org/W2032180390","https://openalex.org/W2051821221","https://openalex.org/W2058485573","https://openalex.org/W2068507382","https://openalex.org/W2071011067","https://openalex.org/W2085116982","https://openalex.org/W2095219480","https://openalex.org/W2114703348","https://openalex.org/W2127087935","https://openalex.org/W2129000925","https://openalex.org/W2480295938","https://openalex.org/W2489640212","https://openalex.org/W2523246573","https://openalex.org/W2608939392","https://openalex.org/W2618749399","https://openalex.org/W2736601468","https://openalex.org/W2765593060","https://openalex.org/W2904246096","https://openalex.org/W2955804429","https://openalex.org/W2964138017","https://openalex.org/W2964340928","https://openalex.org/W3015339458","https://openalex.org/W3026181585","https://openalex.org/W3038926390","https://openalex.org/W3129469040","https://openalex.org/W3152346276","https://openalex.org/W3209165814","https://openalex.org/W4200635288","https://openalex.org/W4206037914","https://openalex.org/W4213269203","https://openalex.org/W4223992650","https://openalex.org/W4225531222","https://openalex.org/W4225874164","https://openalex.org/W4226257065","https://openalex.org/W4281258657","https://openalex.org/W4293731533","https://openalex.org/W4385237431","https://openalex.org/W6727249380","https://openalex.org/W6741002519","https://openalex.org/W6750645735","https://openalex.org/W6840827858"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W4285140130","https://openalex.org/W3104770499","https://openalex.org/W4285677055","https://openalex.org/W1992731528","https://openalex.org/W2007843488","https://openalex.org/W1994436307","https://openalex.org/W1987021796","https://openalex.org/W2795565301","https://openalex.org/W2785349417"],"abstract_inverted_index":{"In":[0,23,114],"this":[1],"article,":[2],"an":[3,137],"adaptive":[4],"optimization":[5,46,138,178],"method":[6,31,47,130],"is":[7,33,48],"proposed":[8,25,77],"for":[9,40,131],"the":[10,20,24,38,45,52,84,96,100,111,118,122,143],"dynamic":[11,64],"resource":[12,67],"allocation":[13,68],"problem":[14],"(RAP)":[15],"with":[16,75,155,180,186,196],"multiple":[17,41],"objectives":[18],"in":[19,55,63,146],"manufacturing":[21],"industry.":[22],"method,":[26],"a":[27,72,76,89,105,128],"novel":[28],"reinforcement":[29,158,168],"learning":[30,159,169],"(DSAC-ERCE)":[32],"designed":[34],"to":[35,50,82,93,109,140,176,182],"adaptively":[36],"set":[37],"weights":[39],"objectives,":[42,184,193],"and":[43,65,102,126,151,194],"then":[44],"adopted":[49],"generate":[51],"noninferior":[53],"solutions":[54],"each":[56],"time":[57],"period.":[58],"To":[59],"ensure":[60],"DSAC-ERCE's":[61],"performance":[62],"complex":[66],"environments,":[69],"we":[70,87,116,149],"develop":[71],"state-encoding":[73],"network":[74],"information":[78],"entropy":[79,107],"attention":[80],"mechanism":[81],"encode":[83],"state.":[85],"Then,":[86],"introduce":[88,136],"new":[90],"reward":[91],"function":[92],"escape":[94],"from":[95],"local":[97],"optima":[98],"of":[99,120,124],"policy":[101,108,112],"further":[103],"present":[104,127],"conditional":[106],"enhance":[110],"network.":[113],"addition,":[115],"demonstrate":[117],"feasibility":[119],"improving":[121],"quality":[123],"actions":[125],"boundary":[129],"high-quality":[132],"actions.":[133],"We":[134],"also":[135],"model":[139],"automatically":[141],"adjust":[142],"temperature":[144],"parameter":[145],"DSAC-ERCE.":[147],"Furthermore,":[148],"compare":[150],"analyze":[152],"our":[153],"approach":[154],"other":[156],"state-of-the-art":[157,167],"methods.":[160,170],"The":[161],"experiments":[162],"illustrate":[163],"that":[164],"DSAC-ERCE":[165,172],"outperforms":[166],"Moreover,":[171],"can":[173],"be":[174],"generalized":[175],"solve":[177],"problems":[179,185,195],"two":[181],"five":[183],"linear,":[187],"quadratic,":[188],"cubic,":[189],"logarithmic,":[190],"or":[191],"inverse":[192],"diverse":[197],"structures.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}