{"id":"https://openalex.org/W7204852289","doi":"https://doi.org/10.1177/03611981261459438","title":"TAWJEEH: An Integrated Deep Reinforcement Learning and Heuristic Framework for Cellular Vehicle-to-Everything Enabled Real-Time Multidepot Vehicle Routing Optimization in Urban Logistics","display_name":"TAWJEEH: An Integrated Deep Reinforcement Learning and Heuristic Framework for Cellular Vehicle-to-Everything Enabled Real-Time Multidepot Vehicle Routing Optimization in Urban Logistics","publication_year":2026,"publication_date":"2026-08-30","ids":{"openalex":"https://openalex.org/W7204852289","doi":"https://doi.org/10.1177/03611981261459438"},"language":"en","primary_location":{"id":"doi:10.1177/03611981261459438","doi":"https://doi.org/10.1177/03611981261459438","is_oa":false,"landing_page_url":"https://doi.org/10.1177/03611981261459438","pdf_url":null,"source":{"id":"https://openalex.org/S145575934","display_name":"Transportation Research Record Journal of the Transportation Research Board","issn_l":"0361-1981","issn":["0361-1981","2169-4052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-scientific","cwts-core","dongbi-b","jufo-1","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportation Research Record: Journal of the Transportation Research Board","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064190189","display_name":"Yacine Harkat","orcid":"https://orcid.org/0009-0001-3046-7790","observed_orcids":["https://orcid.org/0009-0001-3046-7790"]},"institutions":[{"id":"https://openalex.org/I157169809","display_name":"University of Sciences and Technology Houari Boumediene","ror":"https://ror.org/02kb89c09","country_code":"DZ","type":"education","lineage":["https://openalex.org/I157169809"]}],"countries":["DZ"],"is_corresponding":true,"raw_author_name":"Yacine Harkat","raw_affiliation_strings":["USTHB: Universite des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria"],"raw_orcid":"https://orcid.org/0009-0001-3046-7790","affiliations":[{"raw_affiliation_string":"USTHB: Universite des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria","institution_ids":["https://openalex.org/I157169809"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020259367","display_name":"Mustapha Hemis","orcid":"https://orcid.org/0000-0002-6353-0215","observed_orcids":["https://orcid.org/0000-0002-6353-0215"]},"institutions":[{"id":"https://openalex.org/I157169809","display_name":"University of Sciences and Technology Houari Boumediene","ror":"https://ror.org/02kb89c09","country_code":"DZ","type":"education","lineage":["https://openalex.org/I157169809"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Mustapha Hemis","raw_affiliation_strings":["USTHB: Universite des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria"],"raw_orcid":"https://orcid.org/0000-0002-6353-0215","affiliations":[{"raw_affiliation_string":"USTHB: Universite des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria","institution_ids":["https://openalex.org/I157169809"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044010884","display_name":"El\u2010Sedik Lamini","orcid":"https://orcid.org/0000-0001-6786-1110","observed_orcids":["https://orcid.org/0000-0001-6786-1110"]},"institutions":[{"id":"https://openalex.org/I157169809","display_name":"University of Sciences and Technology Houari Boumediene","ror":"https://ror.org/02kb89c09","country_code":"DZ","type":"education","lineage":["https://openalex.org/I157169809"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"El-Sedik Lamini","raw_affiliation_strings":["USTHB: Universite des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria"],"raw_orcid":"https://orcid.org/0000-0001-6786-1110","affiliations":[{"raw_affiliation_string":"USTHB: Universite des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria","institution_ids":["https://openalex.org/I157169809"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087761119","display_name":"Hamza Kheddar","orcid":"https://orcid.org/0000-0002-9532-2453","observed_orcids":["https://orcid.org/0000-0002-9532-2453"]},"institutions":[{"id":"https://openalex.org/I4210128965","display_name":"University Yahia Fares of Medea","ror":"https://ror.org/02e2yc259","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210128965"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Hamza Kheddar","raw_affiliation_strings":["Universite Dr Yahia Fares de Medea, Medea, Algeria"],"raw_orcid":"https://orcid.org/0000-0002-9532-2453","affiliations":[{"raw_affiliation_string":"Universite Dr Yahia Fares de Medea, Medea, Algeria","institution_ids":["https://openalex.org/I4210128965"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064190189"],"corresponding_institution_ids":["https://openalex.org/I157169809"],"apc_list":{"value":3650,"currency":"USD","value_usd":3650},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54859172,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.9761000275611877,"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":0.9761000275611877,"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/T12306","display_name":"Urban and Freight Transport Logistics","score":0.02319999970495701,"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"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.0,"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/deep-reinforcement-learning","display_name":"deep reinforcement learning","score":0.8050000071525574},{"id":"https://openalex.org/keywords/deep-q-network","display_name":"deep Q-network","score":0.8659999966621399},{"id":"https://openalex.org/keywords/city-logistics","display_name":"urban logistics","score":0.6439999938011169},{"id":"https://openalex.org/keywords/real-time-traffic-information","display_name":"real-time traffic information","score":0.6200000047683716},{"id":"https://openalex.org/keywords/clustering-heuristics","display_name":"clustering heuristics","score":0.8410000205039978},{"id":"https://openalex.org/keywords/fuel-conservation","display_name":"fuel consumption reduction","score":0.6359999775886536},{"id":"https://openalex.org/keywords/co2-emissions","display_name":"CO2 emissions","score":0.8080000281333923},{"id":"https://openalex.org/keywords/vehicle-routing-optimization","display_name":"vehicle routing optimization","score":0.42399999499320984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7142000198364258},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6901999711990356},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6194000244140625},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5713000297546387},{"id":"https://openalex.org/C40128228","wikidata":"https://www.wikidata.org/wiki/Q460851","display_name":"Ant colony optimization algorithms","level":2,"score":0.49970000982284546},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4684999883174896},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.45570001006126404},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.36559998989105225},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35569998621940613},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C2778391309","wikidata":"https://www.wikidata.org/wiki/Q7832527","display_name":"Traffic simulation","level":3,"score":0.31859999895095825},{"id":"https://openalex.org/C60891933","wikidata":"https://www.wikidata.org/wiki/Q796575","display_name":"Ant colony","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C86266404","wikidata":"https://www.wikidata.org/wiki/Q7832512","display_name":"Traffic optimization","level":4,"score":0.2734000086784363},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26249998807907104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.25589999556541443},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C192126672","wikidata":"https://www.wikidata.org/wiki/Q1068715","display_name":"Telecommunications network","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/03611981261459438","doi":"https://doi.org/10.1177/03611981261459438","is_oa":false,"landing_page_url":"https://doi.org/10.1177/03611981261459438","pdf_url":null,"source":{"id":"https://openalex.org/S145575934","display_name":"Transportation Research Record Journal of the Transportation Research Board","issn_l":"0361-1981","issn":["0361-1981","2169-4052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-scientific","cwts-core","dongbi-b","jufo-1","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportation Research Record: Journal of the Transportation Research Board","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":1.0,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"},{"score":1.0,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1968686257","https://openalex.org/W2066086285","https://openalex.org/W2111563176","https://openalex.org/W2133415371","https://openalex.org/W2143058845","https://openalex.org/W2178041607","https://openalex.org/W2221980827","https://openalex.org/W2560592986","https://openalex.org/W2911272593","https://openalex.org/W2932902314","https://openalex.org/W2938157874","https://openalex.org/W3004825906","https://openalex.org/W3037428092","https://openalex.org/W3122846486","https://openalex.org/W3128703869","https://openalex.org/W3132134635","https://openalex.org/W3178514907","https://openalex.org/W4214684986","https://openalex.org/W4224138275","https://openalex.org/W4252801674","https://openalex.org/W4296181692","https://openalex.org/W4316654748","https://openalex.org/W4327757829","https://openalex.org/W4383895242","https://openalex.org/W4390494376","https://openalex.org/W4391221820","https://openalex.org/W4401798721","https://openalex.org/W4407959019","https://openalex.org/W4408893441","https://openalex.org/W4410035306","https://openalex.org/W4411554613","https://openalex.org/W4414928438","https://openalex.org/W7140318241"],"related_works":["https://openalex.org/W4413902408","https://openalex.org/W4394601806","https://openalex.org/W7203463970","https://openalex.org/W4416677947","https://openalex.org/W4413428399","https://openalex.org/W7214196280","https://openalex.org/W3116609942","https://openalex.org/W4402223937","https://openalex.org/W7165748672","https://openalex.org/W7161552002"],"abstract_inverted_index":{"Urban":[0],"logistics":[1,205],"are":[2],"increasingly":[3],"strained":[4],"by":[5,64,147],"dynamic":[6],"traffic":[7,91],"conditions":[8],"and":[9,40,71,94,101,120,128,154,173,184],"complex":[10,203],"operational":[11,175],"constraints,":[12],"rendering":[13],"traditional":[14],"optimization":[15,123],"methods":[16],"for":[17,45,60,67,73,135],"the":[18,115,138,189],"multidepot":[19],"capacitated":[20],"vehicle":[21],"routing":[22],"problem":[23],"inadequate.":[24],"This":[25],"paper":[26],"introduces":[27],"TAWJEEH,":[28],"a":[29,52,181],"novel":[30],"hybrid":[31],"framework":[32,50],"that":[33],"integrates":[34],"deep":[35,53],"reinforcement":[36],"learning,":[37],"classical":[38],"heuristics,":[39],"cellular":[41],"vehicle-to-everything":[42],"(C-V2X)":[43],"communications":[44],"time-dependent":[46],"MDCVRP":[47],"optimization.":[48],"The":[49,108],"employs":[51],"Q":[54],"network":[55],"to":[56,89,149,161,179,201],"learn":[57],"adaptive":[58],"policies":[59],"customer-to-vehicle":[61],"assignment,":[62],"complemented":[63],"clustering":[65],"algorithms":[66],"initial":[68],"customer":[69],"grouping":[70],"heuristics":[72],"route":[74],"refinement.":[75],"Leveraging":[76],"real-time":[77],"data":[78],"streams":[79],"from":[80],"C-V2X":[81],"messages,":[82],"TAWJEEH":[83,111,142,177],"dynamically":[84],"adjusts":[85],"routes":[86],"in":[87,131,137,164],"response":[88],"live":[90],"conditions.":[92],"Extensive":[93],"realistic":[95],"simulations":[96],"using":[97],"SUMO":[98],"on":[99],"Hamburg":[100],"Luxembourg":[102,140],"road":[103],"networks":[104],"validate":[105],"our":[106],"approach.":[107],"performance":[109,133],"of":[110,191],"is":[112],"benchmarked":[113],"against":[114,156],"Clarke-Wright":[116],"savings":[117],"(CWS)":[118],"heuristic":[119],"ant":[121],"colony":[122],"(ACO).":[124],"Results":[125],"show":[126],"significant":[127],"consistent":[129],"reductions":[130,163],"key":[132],"metrics;":[134],"instance,":[136],"large-scale":[139],"scenario,":[141],"reduces":[143],"total":[144],"travel":[145,166],"distance":[146],"up":[148],"55.4%":[150],"compared":[151],"with":[152,197],"CWS":[153],"8.9%":[155],"ACO.":[157],"These":[158],"improvements":[159],"translate":[160],"substantial":[162],"cumulative":[165],"time,":[167],"fuel":[168],"consumption,":[169],"CO":[170],"2":[171],"emissions,":[172],"overall":[174],"costs.":[176],"proves":[178],"be":[180],"robust,":[182],"scalable,":[183],"computationally":[185],"efficient":[186],"solution,":[187],"highlighting":[188],"potential":[190],"combining":[192],"advanced":[193],"artificial":[194],"intelligence":[195],"techniques":[196],"vehicular":[198],"communication":[199],"technologies":[200],"address":[202],"urban":[204],"challenges.":[206]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-09-01T00:00:00"}