{"id":"https://openalex.org/W7204925963","doi":"https://doi.org/10.48550/arxiv.2608.30520","title":"Learning-Assisted Congestion-Aware Route Scheduling for Semiconductor Fab Material Control Systems","display_name":"Learning-Assisted Congestion-Aware Route Scheduling for Semiconductor Fab Material Control Systems","publication_year":2026,"publication_date":"2026-08-31","ids":{"openalex":"https://openalex.org/W7204925963","doi":"https://doi.org/10.48550/arxiv.2608.30520"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.30520","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.30520","pdf_url":"https://arxiv.org/pdf/2608.30520","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":"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/2608.30520","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148835045","display_name":"Hao Yin","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148862814","display_name":"Meiqi Tu","orcid":"https://orcid.org/0009-0000-5530-2215","observed_orcids":["https://orcid.org/0009-0000-5530-2215"]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tu, Meiqi","raw_affiliation_strings":["Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079665471","display_name":"Anbang Liu","orcid":"https://orcid.org/0000-0002-5827-4368","observed_orcids":["https://orcid.org/0000-0002-5827-4368"]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Liu, Anbang","raw_affiliation_strings":["Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121647971","display_name":"Shaochong Lin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lin, Shaochong","raw_affiliation_strings":["Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5148857608","display_name":"Max Z. J. Shen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shen, Max Z. J.","raw_affiliation_strings":["Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Data and Systems Engineering , The University of Hong Kong , and is also with The Research Center for Digital Production","institution_ids":["https://openalex.org/I889458895"]}]}],"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9375,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9375,"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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.04569999873638153,"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/T14260","display_name":"Impact of AI and Big Data on Business and Society","score":0.0020000000949949026,"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/congestion-aware-routing","display_name":"congestion-aware routing","score":0.6990000009536743},{"id":"https://openalex.org/keywords/delivery-time-prediction","display_name":"delivery time prediction","score":0.8169999718666077},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"multi-label classification","score":0.3889999985694885},{"id":"https://openalex.org/keywords/material-handling-automation","display_name":"automated material handling","score":0.5989999771118164}],"concepts":[{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6406999826431274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6333000063896179},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5552999973297119},{"id":"https://openalex.org/C22684755","wikidata":"https://www.wikidata.org/wiki/Q847526","display_name":"Queueing theory","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C2778156585","wikidata":"https://www.wikidata.org/wiki/Q174053","display_name":"Relay","level":3,"score":0.42239999771118164},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40880000591278076},{"id":"https://openalex.org/C2780682718","wikidata":"https://www.wikidata.org/wiki/Q16321575","display_name":"Production control","level":3,"score":0.4047999978065491},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.3555999994277954},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.33880001306533813},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C66018809","wikidata":"https://www.wikidata.org/wiki/Q1570432","display_name":"Semiconductor device fabrication","level":3,"score":0.32440000772476196},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3149000108242035},{"id":"https://openalex.org/C2781468064","wikidata":"https://www.wikidata.org/wiki/Q1267117","display_name":"Lead time","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2696000039577484},{"id":"https://openalex.org/C107568181","wikidata":"https://www.wikidata.org/wiki/Q5319000","display_name":"Dynamic priority scheduling","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C117938511","wikidata":"https://www.wikidata.org/wiki/Q3634830","display_name":"Inventory control","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.30520","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.30520","pdf_url":"https://arxiv.org/pdf/2608.30520","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.30520","doi":"https://doi.org/10.48550/arxiv.2608.30520","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.30520","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:2608.30520","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.30520","pdf_url":"https://arxiv.org/pdf/2608.30520","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.8970999717712402,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204925963.pdf","grobid_xml":"https://content.openalex.org/works/W7204925963.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2768008502","https://openalex.org/W2965341826","https://openalex.org/W3124316020"],"related_works":["https://openalex.org/W2884995040","https://openalex.org/W2012218926","https://openalex.org/W7001103874","https://openalex.org/W2998801207","https://openalex.org/W2277091748","https://openalex.org/W7124468330","https://openalex.org/W1593213484","https://openalex.org/W2135728540","https://openalex.org/W4250808025","https://openalex.org/W4403675205"],"abstract_inverted_index":{"Automated":[0],"material":[1,11],"handling":[2],"systems":[3],"in":[4,34,40,156],"semiconductor":[5],"fabs":[6],"are":[7],"operated":[8],"by":[9,44,84,192,199],"a":[10,18,30,70,78,110,157,168,178,184],"control":[12],"system":[13],"(MCS)":[14],"that":[15,113,161],"must":[16],"schedule":[17],"relay":[19,50,87],"route":[20,36,53,92,105],"for":[21],"every":[22],"transport":[23,81],"command":[24],"online,":[25],"before":[26,119],"execution.":[27],"This":[28,67],"is":[29,38],"data-driven":[31],"scheduling":[32],"problem":[33],"which":[35],"cost":[37],"dominated":[39],"the":[41,64,120,174],"upper":[42],"tail":[43],"queueing":[45],"at":[46,63],"heterogeneous,":[47],"partially":[48],"observable":[49],"equipment,":[51],"so":[52],"selection":[54],"requires":[55],"estimating":[56],"both":[57],"delivery":[58,164,189],"time":[59,165,190,198],"and":[60,101,128,131,194],"congestion":[61,73,96],"risk":[62],"decision":[65,181],"moment.":[66,122],"paper":[68],"proposes":[69],"transport-network-aware":[71],"dynamic":[72],"representation":[74,124],"(TN-DCR).":[75],"Built":[76],"on":[77,170],"static":[79],"directed":[80],"graph":[82],"induced":[83],"historically":[85],"observed":[86,117],"segments,":[88],"TN-DCR":[89],"combines":[90],"structural":[91],"priors,":[93],"multi-window":[94],"network-wide":[95],"context,":[97],"route-level":[98],"bottleneck":[99],"exposure,":[100],"an":[102,132,142],"inductive":[103],"graph-aware":[104],"embedding,":[106],"all":[107],"constructed":[108],"under":[109],"prediction-time-safety":[111],"invariant":[112],"admits":[114],"only":[115],"information":[116],"strictly":[118],"prediction":[121],"The":[123,151],"feeds":[125],"separate":[126],"queue-":[127],"transfer-time":[129],"regressors":[130],"ordinal":[133],"multi-label":[134],"classifier":[135],"producing":[136],"calibrated":[137],"multi-threshold":[138],"exceedance":[139],"scores,":[140],"with":[141],"empirical-Bayes":[143],"stock-key":[144],"residual":[145],"correction":[146],"reducing":[147],"systematic":[148],"queue-time":[149],"underprediction.":[150],"predictions":[152],"serve":[153],"as":[154],"costs":[155],"risk-constrained":[158],"route-scheduling":[159],"rule":[160],"minimizes":[162],"predicted":[163],"subject":[166],"to":[167],"bound":[169],"extreme-congestion":[171],"probability,":[172],"embedding":[173],"learned":[175],"predictors":[176],"within":[177],"lightweight":[179],"operations-research":[180],"model.":[182],"In":[183],"controlled":[185],"closed-loop":[186],"evaluation,":[187],"mean":[188],"falls":[191],"16.4\\%":[193],"internal":[195],"resource":[196],"waiting":[197],"22.6\\%":[200],"while":[201],"throughput":[202],"remains":[203],"essentially":[204],"unchanged.":[205]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-02T00:00:00"}