{"id":"https://openalex.org/W4408039773","doi":"https://doi.org/10.3390/e27030251","title":"AlphaRouter: Bridging the Gap Between Reinforcement Learning and Optimization for Vehicle Routing with Monte Carlo Tree Searches","display_name":"AlphaRouter: Bridging the Gap Between Reinforcement Learning and Optimization for Vehicle Routing with Monte Carlo Tree Searches","publication_year":2025,"publication_date":"2025-02-27","ids":{"openalex":"https://openalex.org/W4408039773","doi":"https://doi.org/10.3390/e27030251","pmid":"https://pubmed.ncbi.nlm.nih.gov/40149174"},"language":"en","primary_location":{"id":"doi:10.3390/e27030251","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27030251","pdf_url":"https://www.mdpi.com/1099-4300/27/3/251/pdf?version=1740662720","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/27/3/251/pdf?version=1740662720","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030184151","display_name":"Won\u2010Jun Kim","orcid":"https://orcid.org/0000-0003-3948-7672"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Won-Jun Kim","raw_affiliation_strings":["Hyundai Glovis, Seoul 685-700, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hyundai Glovis, Seoul 685-700, Republic of Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103698521","display_name":"J. H. Jeong","orcid":"https://orcid.org/0009-0002-5670-2653"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Jeong","raw_affiliation_strings":["Department of Industrial Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0002-5670-2653","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081283524","display_name":"T.H. Kim","orcid":"https://orcid.org/0009-0003-7120-9178"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taeyeong Kim","raw_affiliation_strings":["Department of Industrial Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0003-7120-9178","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064844412","display_name":"Kichun Lee","orcid":"https://orcid.org/0000-0002-5184-7151"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kichun Lee","raw_affiliation_strings":["Department of Industrial Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-5184-7151","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5064844412"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03752316,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"3","first_page":"251","last_page":"251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9445000290870667,"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":0.9445000290870667,"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/T10524","display_name":"Traffic control and management","score":0.9189000129699707,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10539","display_name":"Sustainable Supply Chain Management","score":0.911300003528595,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8309298753738403},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.7551066875457764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7032259106636047},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.696910560131073},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.6857277154922485},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5504381656646729},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.4977782070636749},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.43683600425720215},{"id":"https://openalex.org/keywords/vehicle-routing-problem","display_name":"Vehicle routing problem","score":0.41399717330932617},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.40215617418289185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31407973170280457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15788224339485168}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8309298753738403},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.7551066875457764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032259106636047},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.696910560131073},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.6857277154922485},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5504381656646729},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.4977782070636749},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.43683600425720215},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.41399717330932617},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.40215617418289185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31407973170280457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15788224339485168},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e27030251","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27030251","pdf_url":"https://www.mdpi.com/1099-4300/27/3/251/pdf?version=1740662720","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:40149174","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40149174","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:5cc63ea830104a24a4738744b18df65d","is_oa":true,"landing_page_url":"https://doaj.org/article/5cc63ea830104a24a4738744b18df65d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 27, Iss 3, p 251 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11941441","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11941441","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e27030251","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27030251","pdf_url":"https://www.mdpi.com/1099-4300/27/3/251/pdf?version=1740662720","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1504000511","display_name":null,"funder_award_id":"NRF-2018R1A5A7059549","funder_id":"https://openalex.org/F4320321408","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408039773.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4408719353","https://openalex.org/W4388870064","https://openalex.org/W2210139803","https://openalex.org/W4235186151","https://openalex.org/W3119129187","https://openalex.org/W2470251263","https://openalex.org/W4206070139","https://openalex.org/W2193306078","https://openalex.org/W2596350817","https://openalex.org/W2002914572"],"abstract_inverted_index":{"Deep":[0],"reinforcement":[1,73,152],"learning":[2,74,153],"(DRL)":[3],"as":[4],"a":[5,29,33,92,97,105,119],"routing":[6,66,79,127,134],"problem":[7,35,42,54],"solver":[8],"has":[9],"shown":[10],"promising":[11,144],"results":[12],"in":[13],"recent":[14],"studies.":[15],"However,":[16],"an":[17,61],"inherent":[18],"gap":[19,71],"exists":[20],"between":[21,72],"computationally":[22],"driven":[23],"DRL":[24,30],"and":[25,75,87,104,145],"optimization-based":[26],"heuristics.":[27,164],"While":[28],"algorithm":[31],"for":[32,125],"certain":[34],"is":[36,143],"able":[37],"to":[38,51,78,150,162],"solve":[39],"several":[40],"similar":[41],"instances,":[43],"traditional":[44],"optimization":[45],"algorithms":[46],"focus":[47],"on":[48],"optimizing":[49],"solutions":[50,148],"one":[52],"specific":[53],"instance.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59],"propose":[60],"approach,":[62],"AlphaRouter,":[63],"which":[64],"solves":[65],"problems":[67],"while":[68],"bridging":[69],"the":[70,110,126,133,140],"optimization.":[76],"Fitting":[77],"problems,":[80,128],"our":[81],"approach":[82,142],"first":[83],"proposes":[84],"attention-enabled":[85],"policy":[86,93],"value":[88,106],"networks":[89],"consisting":[90],"of":[91],"network":[94,107],"that":[95,108,139],"produces":[96,109],"probability":[98],"distribution":[99],"over":[100],"all":[101],"possible":[102],"nodes":[103],"expected":[111],"distance":[112],"from":[113],"any":[114],"given":[115],"state.":[116],"We":[117],"modify":[118],"Monte":[120],"Carlo":[121],"tree":[122],"search":[123],"(MCTS)":[124],"selectively":[129],"combining":[130],"it":[131],"with":[132,158],"problems.":[135],"Our":[136],"experiments":[137],"demonstrate":[138],"combined":[141],"yields":[146],"better":[147],"compared":[149],"original":[151],"(RL)":[154],"approaches":[155],"without":[156],"MCTS,":[157],"good":[159],"performance":[160],"comparable":[161],"classical":[163]},"counts_by_year":[],"updated_date":"2026-06-24T13:16:06.693445","created_date":"2025-10-10T00:00:00"}