{"id":"https://openalex.org/W4413747405","doi":"https://doi.org/10.1109/tem.2025.3603183","title":"GPT-Augmented Bayesian Reinforcement Learning Framework for Multiobjective Supplier Selection","display_name":"GPT-Augmented Bayesian Reinforcement Learning Framework for Multiobjective Supplier Selection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413747405","doi":"https://doi.org/10.1109/tem.2025.3603183"},"language":"en","primary_location":{"id":"doi:10.1109/tem.2025.3603183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tem.2025.3603183","pdf_url":null,"source":{"id":"https://openalex.org/S154533451","display_name":"IEEE Transactions on Engineering Management","issn_l":"0018-9391","issn":["0018-9391","1558-0040"],"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 Engineering Management","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/A5054245660","display_name":"Chin\u2010Yi Lin","orcid":"https://orcid.org/0000-0002-5308-8531"},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chin-Yi Lin","raw_affiliation_strings":["Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, Texas, TX, USA","Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-5308-8531","affiliations":[{"raw_affiliation_string":"Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, Texas, TX, USA","institution_ids":["https://openalex.org/I164936912"]},{"raw_affiliation_string":"Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052418153","display_name":"Tzu-Liang Tseng","orcid":null},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tzu-Liang Tseng","raw_affiliation_strings":["Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, Texas, TX, USA","Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-3903-529X","affiliations":[{"raw_affiliation_string":"Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, Texas, TX, USA","institution_ids":["https://openalex.org/I164936912"]},{"raw_affiliation_string":"Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007108586","display_name":"Honglun Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Honglun Xu","raw_affiliation_strings":["Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, Texas, TX, USA","Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, Texas, TX, USA","institution_ids":["https://openalex.org/I164936912"]},{"raw_affiliation_string":"Department of Industrial Manufacturing and Systems Engineering, University of Texas at El Paso, El Paso, TX, USA","institution_ids":["https://openalex.org/I164936912"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054245660"],"corresponding_institution_ids":["https://openalex.org/I164936912"],"apc_list":null,"apc_paid":null,"fwci":3.3377,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.92803554,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"3779","last_page":"3804"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9690999984741211,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9690999984741211,"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":0.9593999981880188,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.958899974822998,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7943980097770691},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.658307671546936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5803555250167847},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5624569654464722},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.5140119791030884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5113465189933777},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45877134799957275},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2923312783241272}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7943980097770691},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.658307671546936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5803555250167847},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5624569654464722},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.5140119791030884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5113465189933777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45877134799957275},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2923312783241272},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tem.2025.3603183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tem.2025.3603183","pdf_url":null,"source":{"id":"https://openalex.org/S154533451","display_name":"IEEE Transactions on Engineering Management","issn_l":"0018-9391","issn":["0018-9391","1558-0040"],"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 Engineering Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G277008315","display_name":null,"funder_award_id":"#P120A220044","funder_id":"https://openalex.org/F4320306106","funder_display_name":"U.S. Department of Education"},{"id":"https://openalex.org/G2893673682","display_name":null,"funder_award_id":"#P116S210004","funder_id":"https://openalex.org/F4320306106","funder_display_name":"U.S. Department of Education"},{"id":"https://openalex.org/G4195747565","display_name":null,"funder_award_id":"ERC-ASPIRE-1941524","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5065788867","display_name":null,"funder_award_id":"DUE-2216396","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306106","display_name":"U.S. Department of Education","ror":"https://ror.org/021adze67"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1507099007","https://openalex.org/W1997121831","https://openalex.org/W2460269194","https://openalex.org/W3187483388","https://openalex.org/W3197052056","https://openalex.org/W3202947993","https://openalex.org/W4205329861","https://openalex.org/W4206218462","https://openalex.org/W4206930725","https://openalex.org/W4220729838","https://openalex.org/W4220898681","https://openalex.org/W4308067623","https://openalex.org/W4309005183","https://openalex.org/W4310542789","https://openalex.org/W4382929879","https://openalex.org/W4387630085","https://openalex.org/W4387959528","https://openalex.org/W4392202747","https://openalex.org/W4392806081","https://openalex.org/W4393229110","https://openalex.org/W4393408170","https://openalex.org/W4396585442","https://openalex.org/W4396733217","https://openalex.org/W4396785518","https://openalex.org/W4400146106","https://openalex.org/W4400665082","https://openalex.org/W4401231618","https://openalex.org/W4402729235","https://openalex.org/W4402825912","https://openalex.org/W4405717925","https://openalex.org/W4405850713","https://openalex.org/W4406066647","https://openalex.org/W4407243994","https://openalex.org/W4408492607","https://openalex.org/W4408530798","https://openalex.org/W4409190892","https://openalex.org/W4410042207","https://openalex.org/W4410089205"],"related_works":["https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W2920061524","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856","https://openalex.org/W2145821588","https://openalex.org/W2086122291","https://openalex.org/W1987513656"],"abstract_inverted_index":{"In":[0],"today's":[1],"volatile":[2],"geopolitical":[3,125],"environment":[4],"and":[5,19,53,79,95,114,127,136,178,194,201,232,241],"heightened":[6],"emphasis":[7],"on":[8],"sustainability,":[9],"effective":[10],"supplier":[11,176,230],"selection":[12],"must":[13],"simultaneously":[14],"handle":[15],"cost,":[16],"delivery":[17],"risks,":[18],"ESG":[20,112,129,137,197],"considerations.":[21],"This":[22],"paper":[23,214],"proposes":[24],"a":[25,165,181,216],"GPT-Augmented":[26],"Bayesian":[27,59,93],"Reinforcement":[28,69],"Learning":[29,70],"(i-SUP)":[30],"Framework,":[31],"which":[32],"integrates":[33],"1)":[34],"GPT":[35],"to":[36,49,102,140,174,204],"extract":[37],"real-time":[38],"risk":[39,90,192],"signals":[40,193],"from":[41],"unstructured":[42],"text":[43],"(news,":[44],"social":[45,243],"media),":[46],"2)":[47],"Bayesian-BWM":[48],"capture":[50],"expert":[51],"uncertainty":[52],"produce":[54],"robust":[55],"multi-criteria":[56],"weights,":[57],"3)":[58],"Belief":[60],"Networks":[61],"(BBNs)":[62],"for":[63,72,82],"continuously":[64],"updated":[65],"disruption":[66],"probabilities,":[67],"4)":[68],"(RL)":[71],"dynamic":[73],"monthly":[74],"or":[75,142,157],"weekly":[76],"order":[77],"allocation,":[78],"5)":[80],"NSGA-II":[81],"long-horizon":[83],"multi-objective":[84],"contract":[85,234],"planning.":[86],"By":[87],"combining":[88],"semantic":[89],"detection":[91],"with":[92,208],"updates":[94],"RL-based":[96],"adaptive":[97],"decision-making,":[98],"i-SUP":[99,132],"dynamically":[100],"adjusts":[101],"emergent":[103],"risks":[104],"(e.g.,":[105],"tariffs,":[106],"labor":[107],"unrest),":[108],"while":[109],"concurrently":[110],"balancing":[111],"imperatives":[113],"cost":[115],"efficiency.":[116],"Empirical":[117],"validation":[118],"in":[119,180,228,245],"the":[120,162],"semiconductor":[121],"industry\u2014characterized":[122],"by":[123],"tight":[124],"sensitivity":[126],"high":[128],"demands\u2014shows":[130],"that":[131,149,188,219],"significantly":[133],"reduces":[134],"disruptions":[135],"incidents":[138],"relative":[139],"static":[141],"cost-only":[143],"methods.":[144],"Moreover,":[145],"ablation":[146],"analyses":[147],"confirm":[148],"removing":[150],"any":[151],"single":[152],"module":[153],"(GPT,":[154],"BBN,":[155],"RL,":[156],"NSGA-II)":[158],"undermines":[159],"performance,":[160],"demonstrating":[161],"necessity":[163],"of":[164,184],"fully":[166],"integrated":[167],"pipeline.":[168],"The":[169],"findings":[170],"underscore":[171],"i-SUP's":[172],"ability":[173],"enhance":[175],"resilience":[177],"sustainability":[179,210],"wide":[182],"range":[183],"globalized":[185],"supply":[186,249],"networks":[187],"face":[189],"evolving":[190],"textual":[191],"multi-dimensional":[195],"objectives.":[196],"trade-offs,":[198],"enabling":[199],"boards":[200],"procurement":[202],"leaders":[203],"align":[205],"operational":[206],"policies":[207],"strategic":[209],"goals.":[211],"Overall,":[212],"this":[213],"presents":[215],"policy-relevant":[217],"approach":[218],"informs":[220],"how":[221],"top":[222],"management":[223],"can":[224],"leverage":[225],"artificial":[226],"intelligence":[227],"day-to-day":[229],"decisions":[231],"long-term":[233],"negotiations,":[235],"thereby":[236],"advancing":[237],"both":[238],"financial":[239],"outcomes":[240],"corporate":[242],"responsibility":[244],"high-stakes,":[246],"rapidly":[247],"changing":[248],"networks.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
