{"id":"https://openalex.org/W7201842003","doi":"https://doi.org/10.48550/arxiv.2608.06145","title":"Quantum Amplitude Estimation for Travel Time Estimation in Stochastic Vehicle Routing Problems","display_name":"Quantum Amplitude Estimation for Travel Time Estimation in Stochastic Vehicle Routing Problems","publication_year":2026,"publication_date":"2026-08-06","ids":{"openalex":"https://openalex.org/W7201842003","doi":"https://doi.org/10.48550/arxiv.2608.06145"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2608.06145","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.06145","pdf_url":"https://arxiv.org/pdf/2608.06145","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","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.06145","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5146036398","display_name":"Xingyue Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wang, Xingyue","raw_affiliation_strings":["School of Civil and Environmental Engineering , University of Connecticut , Storrs , CT 06269 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil and Environmental Engineering , University of Connecticut , Storrs , CT 06269 USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073240364","display_name":"Monika Filipovska","orcid":"https://orcid.org/0000-0002-2718-4722","observed_orcids":["https://orcid.org/0000-0002-2718-4722"]},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Filipovska, Monika","raw_affiliation_strings":["School of Civil and Environmental Engineering , University of Connecticut , Storrs , CT 06269 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil and Environmental Engineering , University of Connecticut , Storrs , CT 06269 USA","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I140172145"],"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9775000214576721,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9775000214576721,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.017500000074505806,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quantum-amplitude-estimation","display_name":"quantum amplitude estimation","score":0.9869999885559082},{"id":"https://openalex.org/keywords/stochastic-vehicle-routing-problem","display_name":"stochastic vehicle routing problem","score":0.9390000104904175},{"id":"https://openalex.org/keywords/travel-time-estimation","display_name":"travel time estimation","score":0.9570000171661377},{"id":"https://openalex.org/keywords/hybrid-quantum-classical-optimization","display_name":"hybrid quantum-classical optimization","score":0.8220000267028809},{"id":"https://openalex.org/keywords/intelligent-transportation-systems","display_name":"intelligent transportation systems","score":0.8790000081062317},{"id":"https://openalex.org/keywords/qiskit","display_name":"Qiskit","score":0.7519999742507935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6072999835014343},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.564300000667572},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5539000034332275},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5023000240325928},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.43849998712539673},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.43130001425743103},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.4000999927520752},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3750999867916107},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3650999963283539},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C132725507","wikidata":"https://www.wikidata.org/wiki/Q39879","display_name":"Monte Carlo integration","level":5,"score":0.28349998593330383},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.2563999891281128}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.06145","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.06145","pdf_url":"https://arxiv.org/pdf/2608.06145","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.2608.06145","doi":"https://doi.org/10.48550/arxiv.2608.06145","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.06145","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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.06145","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.06145","pdf_url":"https://arxiv.org/pdf/2608.06145","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.7207000255584717}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2150975100","display_name":"EAGER: Quantum Algorithmic Foundations for Reliable Transportation Networks","funder_award_id":"2520130","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7201842003.pdf","grobid_xml":"https://content.openalex.org/works/W7201842003.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Solving":[0],"the":[1,28,55,59,96,100,166,179,193],"Vehicle":[2],"Routing":[3],"Problem":[4],"(VRP)":[5],"in":[6,14,86,127,212],"Stochastic":[7],"Transportation":[8,16],"Networks":[9],"(STNs),":[10],"a":[11,73,110,114,161],"core":[12],"task":[13],"Intelligent":[15],"Systems":[17],"(ITS),":[18],"introduces":[19],"estimation":[20,85,176],"challenges":[21,34],"for":[22,81,152,206],"stochastic":[23],"path":[24],"travel":[25,61,83,97,106,156],"times":[26],"and":[27,58,71,142,171],"resulting":[29],"VRP":[30],"objective":[31],"function.":[32],"These":[33],"have":[35],"typically":[36],"been":[37],"addressed":[38],"through":[39],"computationally":[40],"expensive":[41],"sampling-based":[42],"techniques":[43],"such":[44],"as":[45],"Monte":[46,119],"Carlo":[47,120],"simulation,":[48],"whose":[49],"performance":[50],"depends":[51],"on":[52,90,160,203],"sample":[53],"size,":[54],"sampling":[56,91],"strategy,":[57],"underlying":[60],"time":[62,84,98,107,157],"distributions.":[63,158],"To":[64],"address":[65],"these":[66],"issues,":[67],"this":[68],"study":[69],"proposes":[70],"validates":[72],"quantum":[74,111],"computing":[75],"technique,":[76],"Quantum":[77],"Amplitude":[78],"Estimation":[79],"(QAE)":[80],"path-level":[82],"STNs.":[87],"Without":[88],"relying":[89],"or":[92],"prior":[93],"assumptions":[94],"of":[95,168],"distribution,":[99],"proposed":[101],"framework":[102],"encodes":[103],"all":[104,187],"feasible":[105],"realizations":[108],"into":[109],"superposition,":[112],"enabling":[113],"theoretical":[115],"quadratic":[116],"speed-up":[117],"over":[118],"simulation.":[121],"Four":[122],"QAE":[123,181],"variants":[124,182],"are":[125],"implemented":[126],"IBM's":[128],"Qiskit":[129],"framework,":[130],"namely":[131],"Canonical":[132],"AE":[133,136,140,144],"(CAE),":[134],"Iterative":[135],"(IAE),":[137],"Maximum":[138],"Likelihood":[139],"(MLAE),":[141],"Faster":[143],"(FAE),":[145],"together":[146],"with":[147,190],"four":[148,180],"rotation-angle":[149,172],"scaling":[150,169],"strategies":[151],"handling":[153],"different":[154],"discrete":[155],"Experiments":[159],"small-scale":[162],"STN":[163],"show":[164],"that":[165],"choice":[167],"method":[170],"range":[173],"significantly":[174],"affects":[175],"accuracy,":[177],"while":[178],"produce":[183],"comparable":[184],"estimates":[185],"across":[186],"tested":[188],"conditions,":[189],"IAE":[191],"exhibiting":[192],"most":[194],"stable":[195],"overall":[196],"performance.":[197],"The":[198],"results":[199],"provide":[200],"practical":[201],"guidance":[202],"parameter":[204],"selection":[205],"future":[207],"hybrid":[208],"quantum-classical":[209],"optimization":[210],"frameworks":[211],"ITS":[213],"applications.":[214]},"counts_by_year":[],"updated_date":"2026-09-30T09:27:27.532063","created_date":"2026-08-08T00:00:00"}