{"id":"https://openalex.org/W4417275901","doi":"https://doi.org/10.48550/arxiv.2507.08316","title":"Approximation Algorithms for the Cumulative Vehicle Routing Problem with Stochastic Demands","display_name":"Approximation Algorithms for the Cumulative Vehicle Routing Problem with Stochastic Demands","publication_year":2025,"publication_date":"2025-07-11","ids":{"openalex":"https://openalex.org/W4417275901","doi":"https://doi.org/10.48550/arxiv.2507.08316"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2507.08316","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.08316","pdf_url":"https://arxiv.org/pdf/2507.08316","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.08316","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069951259","display_name":"Jingyang Zhao","orcid":"https://orcid.org/0000-0002-3566-3336"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Jingyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5033729619","display_name":"Mingyu Xiao","orcid":"https://orcid.org/0000-0002-1012-2373"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Mingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9708999991416931,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9708999991416931,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.004800000227987766,"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/T11502","display_name":"Facility Location and Emergency Management","score":0.004600000102072954,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.7039999961853027},{"id":"https://openalex.org/keywords/vehicle-routing-problem","display_name":"Vehicle routing problem","score":0.6668000221252441},{"id":"https://openalex.org/keywords/randomized-algorithm","display_name":"Randomized algorithm","score":0.590399980545044},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4810999929904938},{"id":"https://openalex.org/keywords/stochastic-approximation","display_name":"Stochastic approximation","score":0.45239999890327454}],"concepts":[{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.7039999961853027},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.6668000221252441},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6305000185966492},{"id":"https://openalex.org/C128669082","wikidata":"https://www.wikidata.org/wiki/Q583461","display_name":"Randomized algorithm","level":2,"score":0.590399980545044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5281000137329102},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4810999929904938},{"id":"https://openalex.org/C55479107","wikidata":"https://www.wikidata.org/wiki/Q97663916","display_name":"Stochastic approximation","level":3,"score":0.45239999890327454},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4449000060558319},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36320000886917114},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.2587999999523163}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2507.08316","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.08316","pdf_url":"https://arxiv.org/pdf/2507.08316","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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.2507.08316","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.08316","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.08316","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.08316","pdf_url":"https://arxiv.org/pdf/2507.08316","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,88],"the":[1,20,28,35,40,44,50,54,57,65,69,80,100,135,153],"Cumulative":[2],"Vehicle":[3,30],"Routing":[4,31],"Problem":[5,32],"(Cu-VRP),":[6],"we":[7,91,125,146,176],"need":[8],"to":[9,22,38,169],"find":[10],"a":[11,15,93,117,123,128,148],"feasible":[12],"itinerary":[13],"for":[14,97,132,180],"capacitated":[16],"vehicle":[17,66],"located":[18],"at":[19],"depot":[21],"satisfy":[23],"customers'":[24],"demand,":[25],"as":[26,122],"in":[27],"well-known":[29],"(VRP),":[33],"but":[34],"goal":[36],"is":[37,47,62,71,86,116,167],"minimize":[39],"cumulative":[41],"cost":[42],"of":[43,59,83,104,120,139,157],"vehicle,":[45],"which":[46],"based":[48],"on":[49],"vehicle's":[51],"load":[52],"throughout":[53],"itinerary.":[55],"If":[56],"demand":[58],"each":[60,165],"customer":[61,166],"unknown":[63],"until":[64],"visits":[67],"it,":[68],"problem":[70],"called":[72],"Cu-VRP":[73],"with":[74,112],"Stochastic":[75,113],"Demands":[76,114],"(Cu-VRPSD).":[77],"Assume":[78],"that":[79],"approximation":[81,102,137,155],"ratio":[82,103,138,156],"metric":[84],"TSP":[85],"$1.5$.":[87],"this":[89],"paper,":[90],"propose":[92],"randomized":[94,129,149],"$3.456$-approximation":[95],"algorithm":[96,131],"Cu-VRPSD,":[98,121],"improving":[99,134,152],"best-known":[101,136,154],"$6$":[105],"(Discret.":[106],"Appl.":[107],"Math.":[108],"2020).":[109],"Since":[110],"VRP":[111],"(VRPSD)":[115],"special":[118],"case":[119],"corollary,":[124],"also":[126],"obtain":[127,177],"$3.25$-approximation":[130],"VRPSD,":[133],"$3.5$":[140],"(Oper.":[141,159],"Res.":[142,160],"2012).":[143],"For":[144],"Cu-VRP,":[145],"give":[147],"$3.194$-approximation":[150],"algorithm,":[151],"$4$":[158],"Lett.":[161],"2013).":[162],"Moreover,":[163],"if":[164],"allowed":[168],"be":[170],"satisfied":[171],"by":[172],"using":[173],"multiple":[174],"tours,":[175],"further":[178],"improvements":[179],"Cu-VRPSD":[181],"and":[182],"Cu-VRP.":[183]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
