{"id":"https://openalex.org/W7133545832","doi":"https://doi.org/10.48550/arxiv.2603.03180","title":"Type-Aware Retrieval-Augmented Generation with Dependency Closure for Solver-Executable Industrial Optimization Modeling","display_name":"Type-Aware Retrieval-Augmented Generation with Dependency Closure for Solver-Executable Industrial Optimization Modeling","publication_year":2026,"publication_date":"2026-03-03","ids":{"openalex":"https://openalex.org/W7133545832","doi":"https://doi.org/10.48550/arxiv.2603.03180"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.03180","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03180","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.03180","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128097019","display_name":"Y. Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Y.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128124457","display_name":"R. Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128071478","display_name":"M. Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128072291","display_name":"Z. Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Z.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128093258","display_name":"YC. Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, YC.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128115114","display_name":"M. C. Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128047490","display_name":"Z. Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Z.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"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":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.14740000665187836,"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"}},"topics":[{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.14740000665187836,"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/T11450","display_name":"Model-Driven Software Engineering Techniques","score":0.11670000106096268,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T11948","display_name":"Machine Learning in Materials Science","score":0.08579999953508377,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6751999855041504},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.6597999930381775},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.600600004196167},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.45419999957084656},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4499000012874603},{"id":"https://openalex.org/keywords/closure","display_name":"Closure (psychology)","score":0.3968999981880188},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.3418000042438507},{"id":"https://openalex.org/keywords/data-integrity","display_name":"Data integrity","score":0.33970001339912415},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.3327000141143799}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7773000001907349},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6751999855041504},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6597999930381775},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.600600004196167},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.45419999957084656},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4499000012874603},{"id":"https://openalex.org/C146834321","wikidata":"https://www.wikidata.org/wiki/Q2979672","display_name":"Closure (psychology)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3573000133037567},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.3084999918937683},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3018999993801117},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2955000102519989},{"id":"https://openalex.org/C164155591","wikidata":"https://www.wikidata.org/wiki/Q2067766","display_name":"Satisfiability modulo theories","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28529998660087585},{"id":"https://openalex.org/C207850805","wikidata":"https://www.wikidata.org/wiki/Q269608","display_name":"Reverse engineering","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27140000462532043},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.03180","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03180","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.03180","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03180","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6070207357406616}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automated":[0],"industrial":[1,127],"optimization":[2,131,216],"modeling":[3,41],"requires":[4],"reliable":[5],"translation":[6],"of":[7,107],"natural-language":[8,92],"requirements":[9],"into":[10,78],"solver-executable":[11,112],"code.":[12],"However,":[13],"large":[14,210],"language":[15,211],"models":[16,20,174,212],"often":[17],"generate":[18],"non-compilable":[19],"due":[21],"to":[22,48,208],"missing":[23],"declarations,":[24],"type":[25],"inconsistencies,":[26],"and":[27,44,75,81,98,135,153,201],"incomplete":[28],"dependency":[29,46,115,193],"contexts.":[30],"We":[31,120],"propose":[32],"a":[33,62,87,91,100,205],"type-aware":[34,192],"retrieval-augmented":[35],"generation":[36],"(RAG)":[37],"method":[38,60,123,145],"that":[39,55,175,190],"enforces":[40],"entity":[42],"types":[43],"minimal":[45,101],"closure":[47,194],"ensure":[49],"executability.":[50],"Unlike":[51],"existing":[52],"RAG":[53,163],"approaches":[54],"index":[56],"unstructured":[57],"text,":[58],"our":[59,144],"constructs":[61],"domain-specific":[63],"typed":[64,79,108],"knowledge":[65,88],"base":[66],"by":[67],"parsing":[68],"heterogeneous":[69],"sources,":[70],"such":[71],"as":[72],"academic":[73],"papers":[74],"solver":[76],"code,":[77,113],"units":[80],"encoding":[82],"their":[83],"mathematical":[84],"dependencies":[85],"in":[86,132,213],"graph.":[89,119],"Given":[90],"instruction,":[93],"it":[94,170],"performs":[95],"hybrid":[96],"retrieval":[97],"computes":[99],"dependency-closed":[102],"context,":[103],"the":[104,118,122,141,167],"smallest":[105],"set":[106],"symbols":[109],"required":[110],"for":[111,197],"via":[114],"propagation":[116],"over":[117],"validate":[121],"on":[124],"two":[125],"constraint-intensive":[126],"cases:":[128],"demand":[129],"response":[130],"battery":[133],"production":[134],"flexible":[136],"job":[137],"shop":[138],"scheduling.":[139],"In":[140,166],"first":[142],"case,":[143,169],"generates":[146],"an":[147],"executable":[148],"model":[149],"incorporating":[150],"demand-response":[151],"incentives":[152],"load-reduction":[154],"constraints,":[155],"achieving":[156],"peak":[157],"shaving":[158],"while":[159],"preserving":[160],"profitability;":[161],"conventional":[162],"baselines":[164,184],"fail.":[165],"second":[168],"consistently":[171],"produces":[172],"compilable":[173],"reach":[176],"known":[177],"optimal":[178],"solutions,":[179],"demonstrating":[180],"robust":[181],"cross-domain":[182],"generalization;":[183],"fail":[185],"entirely.":[186],"Ablation":[187],"studies":[188],"confirm":[189],"enforcing":[191],"is":[195],"essential":[196],"avoiding":[198],"structural":[199],"hallucinations":[200],"ensuring":[202],"executability,":[203],"addressing":[204],"critical":[206],"barrier":[207],"deploying":[209],"complex":[214],"engineering":[215],"tasks.":[217]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-05T00:00:00"}
