{"id":"https://openalex.org/W7208777486","doi":"https://doi.org/10.48550/arxiv.2609.03754","title":"Automated Priority Rule Design for the Resource-Constrained Project Scheduling Problem: A Large Language Model-Guided Population-Based Search","display_name":"Automated Priority Rule Design for the Resource-Constrained Project Scheduling Problem: A Large Language Model-Guided Population-Based Search","publication_year":2026,"publication_date":"2026-09-03","ids":{"openalex":"https://openalex.org/W7208777486","doi":"https://doi.org/10.48550/arxiv.2609.03754"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.03754","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.03754","pdf_url":"https://arxiv.org/pdf/2609.03754","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.03754","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5150005668","display_name":"Jingyu Luo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Luo, Jingyu","raw_affiliation_strings":["COSMO -Stochastic Mine Planning Laboratory , McGill University , 3450 Rue University , H3A 0E8 Montreal ( Canada )"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"COSMO -Stochastic Mine Planning Laboratory , McGill University , 3450 Rue University , H3A 0E8 Montreal ( Canada )","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034353692","display_name":"Mario Vanhoucke","orcid":"https://orcid.org/0000-0001-6702-3563","observed_orcids":["https://orcid.org/0000-0001-6702-3563"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vanhoucke, Mario","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5014342657","display_name":"Jose' Coelho","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Coelho, Jos\u00e9","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T12177","display_name":"Resource-Constrained Project Scheduling","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12177","display_name":"Resource-Constrained Project Scheduling","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.008200000040233135,"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/T12401","display_name":"Scheduling and Timetabling Solutions","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/resource-constrained-project-scheduling-problem","display_name":"resource-constrained project scheduling","score":0.9449999928474426},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9850000143051147},{"id":"https://openalex.org/keywords/hyper-heuristics","display_name":"hyper-heuristics","score":0.824999988079071},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"genetic programming","score":0.7070000171661377},{"id":"https://openalex.org/keywords/population-based-search","display_name":"population-based search","score":0.9070000052452087},{"id":"https://openalex.org/keywords/makespan-minimization","display_name":"makespan minimization","score":0.8799999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520999908447266},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7038999795913696},{"id":"https://openalex.org/C149271511","wikidata":"https://www.wikidata.org/wiki/Q1417149","display_name":"Rule-based system","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.4424999952316284},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.43880000710487366},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.43849998712539673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43290001153945923},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4088999927043915},{"id":"https://openalex.org/C89246107","wikidata":"https://www.wikidata.org/wiki/Q1398821","display_name":"Rule of thumb","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32910001277923584},{"id":"https://openalex.org/C15952604","wikidata":"https://www.wikidata.org/wiki/Q179012","display_name":"Project management","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.03754","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.03754","pdf_url":"https://arxiv.org/pdf/2609.03754","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.03754","doi":"https://doi.org/10.48550/arxiv.2609.03754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.03754","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.03754","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.03754","pdf_url":"https://arxiv.org/pdf/2609.03754","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G6512152896","display_name":null,"funder_award_id":"239019","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320310638","display_name":"McGill University","ror":"https://ror.org/01pxwe438"},{"id":"https://openalex.org/F4320320994","display_name":"Canada Research Chairs","ror":"https://ror.org/0517h6h17"},{"id":"https://openalex.org/F4320330273","display_name":"Institut de Valorisation des Donn\u00e9es","ror":"https://ror.org/05a3srq89"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7208777486.pdf","grobid_xml":"https://content.openalex.org/works/W7208777486.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W4390647620"],"related_works":["https://openalex.org/W4221040214","https://openalex.org/W2773606106","https://openalex.org/W2898285076","https://openalex.org/W2915625821","https://openalex.org/W4378417551","https://openalex.org/W6997107295","https://openalex.org/W2032759759","https://openalex.org/W2607123884","https://openalex.org/W3093668234","https://openalex.org/W2394450198"],"abstract_inverted_index":{"The":[0],"objective":[1],"of":[2,149,246],"the":[3,70,88,123,147,150,152,172,180,231,241,247],"resource-constrained":[4],"project":[5],"scheduling":[6],"problem":[7],"(RCPSP)":[8],"is":[9,155],"to":[10,42,73,101,160,230],"minimize":[11],"makespan":[12],"while":[13,133,192,237],"satisfying":[14],"precedence":[15],"and":[16,28,38,56,103,129,142,157,183,215,243],"renewable-resource":[17],"constraints.":[18],"Priority-rule":[19],"heuristics":[20],"construct":[21],"feasible":[22],"schedules":[23],"with":[24,195],"low":[25],"computational":[26],"cost":[27],"explicit":[29],"decision":[30,244],"logic,":[31],"making":[32],"them":[33],"widely":[34],"used":[35],"in":[36,93],"practice":[37],"an":[39,114,126],"attractive":[40],"alternative":[41],"more":[43],"computationally":[44],"intensive":[45],"methods.":[46],"However,":[47],"no":[48],"traditional":[49,176,213],"rule":[50,80,154,238],"performs":[51],"consistently":[52],"well":[53],"across":[54,179],"projects,":[55,206],"researchers":[57],"have":[58,68],"therefore":[59],"investigated":[60],"automated":[61,119],"priority-rule":[62,120],"design.":[63,121],"Genetic":[64],"programming":[65],"(GP)":[66],"hyper-heuristics":[67],"been":[69],"predominant":[71],"approach":[72],"this":[74],"task,":[75],"but":[76],"evolving":[77],"a":[78,199],"high-performing":[79],"may":[81],"require":[82],"evaluating":[83],"many":[84],"candidate":[85,131,140],"rules":[86,107,174,178,186,196,209,214],"on":[87,136,220],"training":[89,137],"projects.":[90,223],"Recent":[91],"advances":[92],"large":[94,205],"language":[95],"models":[96],"(LLMs)":[97],"make":[98],"it":[99],"possible":[100],"generate":[102],"iteratively":[104],"revise":[105],"priority":[106],"using":[108],"performance":[109],"feedback.":[110],"This":[111],"paper":[112],"presents":[113],"LLM-guided":[115],"population-based":[116],"framework":[117],"for":[118],"During":[122],"offline":[124],"search,":[125,151],"LLM":[127,167],"generates":[128],"revises":[130],"rules,":[132],"schedule":[134],"quality":[135],"projects":[138,162],"determines":[139],"fitness":[141],"guides":[143],"subsequent":[144],"revisions.":[145],"At":[146],"end":[148],"best":[153],"returned":[156],"applied":[158],"directly":[159],"unseen":[161],"without":[163],"further":[164],"search":[165,190,233],"or":[166],"calls.":[168],"Experiments":[169],"show":[170],"that":[171],"LLM-designed":[173,208,248],"outperform":[175,184,210],"single":[177],"test":[181],"sets":[182],"GP-designed":[185],"obtained":[187,197],"under":[188],"comparable":[189],"effort,":[191],"remaining":[193],"competitive":[194],"from":[198],"substantially":[200],"larger":[201],"GP":[202],"search.":[203],"On":[204],"selected":[207],"all":[211],"considered":[212],"two":[216],"genetic":[217],"algorithm":[218],"configurations":[219],"highly":[221],"parallel":[222],"An":[224],"ablation":[225],"study":[226],"examines":[227],"how":[228],"changes":[229],"main":[232],"components":[234],"affect":[235],"performance,":[236],"analyses":[239],"describe":[240],"structure":[242],"behavior":[245],"rules.":[249]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-05T00:00:00"}
