{"id":"https://openalex.org/W7133150372","doi":"https://doi.org/10.3390/systems14030261","title":"Research on Distribution Optimization Strategy of Front Warehouse Model Based on Deep Reinforcement Learning","display_name":"Research on Distribution Optimization Strategy of Front Warehouse Model Based on Deep Reinforcement Learning","publication_year":2026,"publication_date":"2026-02-28","ids":{"openalex":"https://openalex.org/W7133150372","doi":"https://doi.org/10.3390/systems14030261"},"language":"en","primary_location":{"id":"doi:10.3390/systems14030261","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14030261","pdf_url":"https://www.mdpi.com/2079-8954/14/3/261/pdf","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"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":"Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-8954/14/3/261/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127773391","display_name":"Jiaqing Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqing Chen","raw_affiliation_strings":["School of Economics and Finance, Xi\u2019an Jiaotong University, Xi\u2019an 710061, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Finance, Xi\u2019an Jiaotong University, Xi\u2019an 710061, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127741593","display_name":"Ming Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Jiang","raw_affiliation_strings":["School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350118, China","institution_ids":["https://openalex.org/I83791580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5127749842","display_name":"Guorong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guorong Chen","raw_affiliation_strings":["School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350118, China"],"raw_orcid":"https://orcid.org/0009-0005-5041-9760","affiliations":[{"raw_affiliation_string":"School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350118, China","institution_ids":["https://openalex.org/I83791580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24913635,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"3","first_page":"261","last_page":"261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9560999870300293,"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":0.9560999870300293,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.008500000461935997,"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":0.0035000001080334187,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7860999703407288},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49459999799728394},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.4503999948501587},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.44859999418258667},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4438999891281128},{"id":"https://openalex.org/keywords/vehicle-routing-problem","display_name":"Vehicle routing problem","score":0.426800012588501},{"id":"https://openalex.org/keywords/variable-neighborhood-search","display_name":"Variable neighborhood search","score":0.4025999903678894},{"id":"https://openalex.org/keywords/temporal-difference-learning","display_name":"Temporal difference learning","score":0.40139999985694885},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.3700999915599823},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.364300012588501}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7860999703407288},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6413000226020813},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5552999973297119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5210000276565552},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.4503999948501587},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4438999891281128},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.426800012588501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41929998993873596},{"id":"https://openalex.org/C2776435737","wikidata":"https://www.wikidata.org/wiki/Q7915703","display_name":"Variable neighborhood search","level":3,"score":0.4025999903678894},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.40139999985694885},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3149999976158142},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/systems14030261","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14030261","pdf_url":"https://www.mdpi.com/2079-8954/14/3/261/pdf","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"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":"Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:249ce28c6a4241ddb07f4ba5a535ea24","is_oa":true,"landing_page_url":"https://doaj.org/article/249ce28c6a4241ddb07f4ba5a535ea24","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":"Systems, Vol 14, Iss 3, p 261 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/systems14030261","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14030261","pdf_url":"https://www.mdpi.com/2079-8954/14/3/261/pdf","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"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":"Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6780414971","display_name":null,"funder_award_id":"S90032600821","funder_id":"https://openalex.org/F4320325142","funder_display_name":"Fujian University of Technology"}],"funders":[{"id":"https://openalex.org/F4320325142","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7133150372.pdf","grobid_xml":"https://content.openalex.org/works/W7133150372.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,50],"multi-depot":[1],"vehicle":[2],"routing":[3],"problem":[4,61],"with":[5,119],"soft":[6],"time":[7,111],"windows":[8],"(MDVRPSTW)":[9],"has":[10],"long":[11],"been":[12],"a":[13,24,58,63,145],"focus":[14],"in":[15,46,185,200,214],"both":[16,201],"academic":[17],"and":[18,34,80,84,166,190,204],"industrial":[19],"circles.":[20],"This":[21],"paper":[22],"proposes":[23],"deep":[25],"reinforcement":[26,87],"learning":[27,88],"framework":[28,51],"designed":[29],"to":[30,116,147,159,163,183],"enhance":[31],"the":[32,40,54,95,120,125,186],"efficiency":[33],"quality":[35,203],"of":[36,42,177,188],"MDVRPSTW":[37,213],"solutions,":[38],"addressing":[39],"limitations":[41],"traditional":[43],"heuristic":[44],"algorithms":[45,165],"large-scale":[47],"complex":[48,215],"scenarios.":[49,216],"first":[52],"transforms":[53],"mathematical":[55],"model":[56,90],"into":[57],"sequential":[59],"decision-making":[60],"through":[62],"Markov":[64],"decision":[65],"process,":[66],"then":[67],"extracts":[68],"path":[69],"selection":[70],"strategies":[71],"using":[72],"an":[73,208],"encoder\u2013decoder":[74],"architecture":[75],"based":[76],"on":[77,94],"attention":[78],"mechanisms":[79],"graph":[81],"neural":[82],"networks,":[83],"employs":[85],"unsupervised":[86],"for":[89,101,212],"training.":[91],"Test":[92],"results":[93],"Solomon":[96],"benchmark":[97],"dataset":[98],"demonstrate":[99],"that":[100],"small-scale":[102],"problems":[103,138],"(N":[104,139],"=":[105,140],"20),":[106],"our":[107,142,169],"method":[108,143,195],"reduces":[109,171],"solving":[110],"by":[112,174],"over":[113,151],"96%":[114],"compared":[115],"comparative":[117],"algorithms,":[118],"objective":[121],"value":[122],"difference":[123],"from":[124],"generalized":[126],"variable":[127],"neighborhood":[128],"search":[129],"(GVNS)":[130],"being":[131],"less":[132],"than":[133],"9%.":[134],"For":[135],"medium-to-large":[136],"scale":[137],"50/100),":[141],"achieves":[144],"27.7":[146],"96.3":[148],"percent":[149],"improvement":[150],"GVNS,":[152],"maintaining":[153],"stable":[154],"solution":[155,202,211],"times":[156],"within":[157],"3":[158],"10":[160],"s.":[161],"Compared":[162],"exact":[164],"meta-heuristic":[167],"methods,":[168],"approach":[170],"computational":[172,205],"costs":[173],"2\u20133":[175],"orders":[176],"magnitude":[178],"while":[179],"demonstrating":[180],"strong":[181],"adaptability":[182],"variations":[184],"number":[187],"depots":[189],"vehicles.":[191],"In":[192],"summary,":[193],"this":[194],"significantly":[196],"outperforms":[197],"baseline":[198],"models":[199],"efficiency,":[206],"providing":[207],"efficient":[209],"end-to-end":[210]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-02T00:00:00"}
