{"id":"https://openalex.org/W7140226254","doi":"https://doi.org/10.48550/arxiv.2603.21533","title":"Non-Exclusive Notifications for Ride-Hailing at Lyft I: Single-Cycle Approximation Algorithms","display_name":"Non-Exclusive Notifications for Ride-Hailing at Lyft I: Single-Cycle Approximation Algorithms","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140226254","doi":"https://doi.org/10.48550/arxiv.2603.21533"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21533","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21533","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21533","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ekbatani, Farbod","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ekbatani, Farbod","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Niazadeh, Rad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niazadeh, Rad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Golari, Mehdi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Golari, Mehdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Camilleri, Romain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Camilleri, Romain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jehl, Titouan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jehl, Titouan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sholley, Chris","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sholley, Chris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Leventi, Matthew","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leventi, Matthew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Calderon, Theresa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Calderon, Theresa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lam, Angela","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lam, Angela","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Duclos, Paul Havard","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duclos, Paul Havard","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Holland, Tim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Holland, Tim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Koch, James","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koch, James","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Reddy, Shreya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Shreya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":13,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.8410999774932861,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11942","display_name":"Transportation and Mobility Innovations","score":0.8410999774932861,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T13553","display_name":"Age of Information Optimization","score":0.04639999940991402,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.023800000548362732,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/approximation-algorithm","display_name":"Approximation algorithm","score":0.6539000272750854},{"id":"https://openalex.org/keywords/polynomial-time-approximation-scheme","display_name":"Polynomial-time approximation scheme","score":0.6061999797821045},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.574400007724762},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5594000220298767},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.5145000219345093},{"id":"https://openalex.org/keywords/monotone-polygon","display_name":"Monotone polygon","score":0.47920000553131104},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.45579999685287476},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4293999969959259},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4154999852180481}],"concepts":[{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.6539000272750854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6169000267982483},{"id":"https://openalex.org/C99140742","wikidata":"https://www.wikidata.org/wiki/Q843550","display_name":"Polynomial-time approximation scheme","level":3,"score":0.6061999797821045},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.574400007724762},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5594000220298767},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5249999761581421},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.5145000219345093},{"id":"https://openalex.org/C2834757","wikidata":"https://www.wikidata.org/wiki/Q4925424","display_name":"Monotone polygon","level":2,"score":0.47920000553131104},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.45579999685287476},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34599998593330383},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.3206000030040741},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.2775000035762787},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C186027771","wikidata":"https://www.wikidata.org/wiki/Q4008379","display_name":"Valuation (finance)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C100808899","wikidata":"https://www.wikidata.org/wiki/Q1192100","display_name":"Set cover problem","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C52692508","wikidata":"https://www.wikidata.org/wiki/Q1333872","display_name":"Combinatorial optimization","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21533","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21533","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21533","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21533","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":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7499704957008362,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Ride-hailing":[0],"platforms":[1],"increasingly":[2],"rely":[3],"on":[4,252,256],"non-exclusive":[5],"notifications-broadcasting":[6],"a":[7,27,41,112,131,142,163,186,193,238],"single":[8,42],"request":[9],"to":[10,54,81,208],"multiple":[11],"drivers":[12,53],"simultaneously-to":[13],"mitigate":[14],"inefficiencies":[15],"caused":[16],"by":[17,77,93],"uncertain":[18],"driver":[19],"acceptance.":[20],"In":[21],"this":[22,63,201],"paper,":[23],"the":[24,35,46,49,79,82,95,138,148,155,179,210,217,227,244],"first":[25,83],"in":[26,216,234],"two-part":[28],"collaboration":[29],"with":[30,168],"Lyft,":[31],"we":[32,121,129,176,198,203,224],"formally":[33],"model":[34,167],"'Notification":[36],"Set":[37],"Selection":[38],"Problem'":[39],"for":[40,56,137,147,200],"decision":[43],"cycle,":[44],"where":[45],"platform":[47],"determines":[48],"optimal":[50],"subset":[51],"of":[52,171,220],"notify":[55],"each":[57],"incoming":[58],"ride":[59,80],"request.":[60],"We":[61,99,152,242],"analyze":[62],"combinatorial":[64],"optimization":[65],"problem":[66,229],"under":[67,104],"two":[68],"contention-resolution":[69],"protocols:":[70],"'First":[71],"Acceptance":[72,87],"(FA)',":[73],"which":[74,89],"prioritizes":[75,90],"speed":[76],"assigning":[78],"responder,":[84],"and":[85,141,183,255],"'Best":[86],"(BA)',":[88],"match":[91],"quality":[92],"selecting":[94],"highest-valued":[96],"accepting":[97],"driver.":[98],"show":[100,204,225],"that":[101,154,178,197,226],"welfare":[102],"maximization":[103],"both":[105],"mechanisms":[106],"is":[107,181,206],"strongly":[108],"NP-hard,":[109],"ruling":[110],"out":[111],"Fully":[113],"Polynomial":[114,132],"Time":[115,133],"Approximation":[116,134],"Scheme":[117,135],"(FPTAS).":[118],"Despite":[119],"this,":[120],"derive":[122],"several":[123],"positive":[124],"algorithmic":[125],"results.":[126],"For":[127,174],"FA,":[128],"present":[130],"(PTAS)":[136],"single-rider":[139],"case":[140,219],"constant-factor":[143],"approximation":[144],"(factor":[145],"4)":[146],"general":[149],"matching":[150],"setting.":[151],"highlight":[153],"FA":[156],"valuation":[157],"function":[158],"can":[159,230],"be":[160,231],"viewed":[161],"as":[162],"novel":[164],"discrete":[165],"choice":[166],"theoretical":[169],"properties":[170],"independent":[172],"interest.":[173],"BA,":[175],"prove":[177],"objective":[180],"monotone":[182],"submodular,":[184],"admitting":[185],"standard":[187],"$(1":[188,211],"-":[189,212],"1/e)$-approximation.":[190],"Moreover,":[191],"using":[192,259],"polynomial-time":[194],"demand":[195],"oracle":[196],"design":[199],"problem,":[202],"it":[205],"possible":[207],"surpass":[209],"1/e)$":[213],"barrier.":[214],"Finally,":[215],"special":[218],"homogeneous":[221],"acceptance":[222],"probabilities,":[223],"BA":[228],"solved":[232],"exactly":[233],"polynomial":[235],"time":[236],"via":[237],"linear":[239],"programming":[240],"formulation.":[241],"validate":[243],"empirical":[245],"performance":[246],"our":[247],"algorithms":[248],"through":[249],"numerical":[250],"experiments":[251],"synthetic":[253],"data":[254,262],"instances":[257],"calibrated":[258],"real":[260],"ride-sharing":[261],"from":[263],"Lyft.":[264]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-25T00:00:00"}