{"id":"https://openalex.org/W4413506043","doi":"https://doi.org/10.3390/sym17091382","title":"A New Vehicle\u2013Multi-Drone Collaborative Delivery Path Optimization Approach","display_name":"A New Vehicle\u2013Multi-Drone Collaborative Delivery Path Optimization Approach","publication_year":2025,"publication_date":"2025-08-24","ids":{"openalex":"https://openalex.org/W4413506043","doi":"https://doi.org/10.3390/sym17091382"},"language":"en","primary_location":{"id":"doi:10.3390/sym17091382","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17091382","pdf_url":"https://www.mdpi.com/2073-8994/17/9/1382/pdf?version=1756100190","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/17/9/1382/pdf?version=1756100190","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100325436","display_name":"Jinhui Li","orcid":"https://orcid.org/0000-0002-2196-9422"},"institutions":[{"id":"https://openalex.org/I167383011","display_name":"Henan University of Science and Technology","ror":"https://ror.org/05d80kz58","country_code":"CN","type":"education","lineage":["https://openalex.org/I167383011"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Li","raw_affiliation_strings":["College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China"],"raw_orcid":"https://orcid.org/0000-0002-2196-9422","affiliations":[{"raw_affiliation_string":"College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China","institution_ids":["https://openalex.org/I167383011"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100709563","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-9193-3652"},"institutions":[{"id":"https://openalex.org/I167383011","display_name":"Henan University of Science and Technology","ror":"https://ror.org/05d80kz58","country_code":"CN","type":"education","lineage":["https://openalex.org/I167383011"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Wang","raw_affiliation_strings":["College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China","institution_ids":["https://openalex.org/I167383011"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100709563"],"corresponding_institution_ids":["https://openalex.org/I167383011"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":5.8432,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95596498,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"17","issue":"9","first_page":"1382","last_page":"1382"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11133","display_name":"UAV Applications and Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9988999962806702,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.7850809693336487},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6394753456115723},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4652358591556549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.324165403842926},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.14338287711143494},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12588804960250854}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.7850809693336487},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6394753456115723},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4652358591556549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.324165403842926},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.14338287711143494},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12588804960250854},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/sym17091382","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17091382","pdf_url":"https://www.mdpi.com/2073-8994/17/9/1382/pdf?version=1756100190","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/sym17091382","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17091382","pdf_url":"https://www.mdpi.com/2073-8994/17/9/1382/pdf?version=1756100190","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413506043.pdf","grobid_xml":"https://content.openalex.org/works/W4413506043.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1977319619","https://openalex.org/W2114572923","https://openalex.org/W2245682929","https://openalex.org/W2342478160","https://openalex.org/W2551686796","https://openalex.org/W2905390834","https://openalex.org/W2905789584","https://openalex.org/W2963421154","https://openalex.org/W3094704314","https://openalex.org/W3095037549","https://openalex.org/W3101957802","https://openalex.org/W3125377832","https://openalex.org/W3125535900","https://openalex.org/W4210588426","https://openalex.org/W4285290966","https://openalex.org/W4293499165","https://openalex.org/W4309034018","https://openalex.org/W4377090877","https://openalex.org/W4379140870","https://openalex.org/W4382365344","https://openalex.org/W4386053882","https://openalex.org/W4388535123","https://openalex.org/W4388766824","https://openalex.org/W4389058205","https://openalex.org/W4390405275","https://openalex.org/W4394627581","https://openalex.org/W4396919365","https://openalex.org/W4398181859","https://openalex.org/W4398768421","https://openalex.org/W4403355727","https://openalex.org/W4404226368","https://openalex.org/W4405989471","https://openalex.org/W4408687771","https://openalex.org/W4409457058","https://openalex.org/W4410444035","https://openalex.org/W4411096401"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4229448053","https://openalex.org/W4247925126","https://openalex.org/W4327774218","https://openalex.org/W2059768187","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W4379143281"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,21,40,105,119,135,142,160,174,178],"logistical":[3],"challenges":[4],"of":[5,23,42,107,124,177,189],"traffic":[6],"congestion":[7],"and":[8,46,59,73,101,113,116,130,154,172,204],"environmental":[9],"concerns":[10],"associated":[11],"with":[12,71,148,201],"carbon":[13],"emissions":[14],"in":[15,55,168],"last-mile":[16],"delivery,":[17],"this":[18],"paper":[19],"explores":[20],"potential":[22],"vehicle\u2013drone":[24],"cooperative":[25],"delivery.":[26],"The":[27],"existing":[28],"studies":[29],"are":[30],"predominantly":[31],"confined":[32],"to":[33,37,51,95,133,165,183,210],"single-drone":[34],"scenarios,":[35],"failing":[36],"simultaneously":[38],"consider":[39],"constraints":[41],"drone":[43,190,195],"payload":[44,72,191,196],"capacity":[45,197],"endurance.":[47],"This":[48],"limitation":[49],"leads":[50],"task":[52],"allocation":[53],"imbalance":[54],"large-scale":[56],"customer":[57,207],"deliveries":[58],"low":[60],"distribution":[61],"efficiency.":[62,140],"Firstly,":[63],"a":[64,91,149],"mathematical":[65],"model":[66],"for":[67],"vehicle\u2013multi-drone":[68],"collaborative":[69],"delivery":[70,202],"endurance":[74],"constraint":[75],"(VMDCD-PEC)":[76],"is":[77,85,198],"proposed.":[78],"Secondly,":[79],"an":[80,187],"improved":[81],"genetic":[82,151],"algorithm":[83,152],"(IGA)":[84],"developed,":[86],"as":[87],"follows:":[88],"1.":[89],"designing":[90],"hybrid":[92],"selection":[93],"strategy":[94],"achieve":[96],"symmetrical":[97],"equilibrium":[98],"between":[99],"exploration":[100],"exploitation":[102],"by":[103,181],"adjusting":[104],"weights":[106],"dynamic":[108],"fitness\u2013distance":[109],"balance,":[110],"greedy":[111],"selection,":[112],"random":[114,131],"selection;":[115],"2.":[117],"introducing":[118],"local":[120],"search":[121,158],"operator":[122],"composed":[123],"gene":[125],"sequence":[126],"reversal,":[127],"single-gene":[128],"slide-down,":[129],"half-swap":[132],"improve":[134],"neighborhood":[136,157],"quality":[137],"solution":[138,180],"mining":[139],"Finally,":[141],"experimental":[143],"results":[144],"show":[145],"that":[146,194,205],"compared":[147],"traditional":[150],"(GA)":[153],"adaptive":[155],"large":[156],"(ALNS),":[159],"IGA":[161],"requires":[162],"less":[163],"time":[164],"find":[166],"solutions":[167],"various":[169],"test":[170],"cases":[171],"reduces":[173],"average":[175],"cost":[176],"optimal":[179],"up":[182],"30%.":[184],"In":[185],"addition,":[186],"analysis":[188],"sensitivity":[192],"showed":[193],"negatively":[199],"correlated":[200],"time,":[203],"larger":[206],"sizes":[208],"corresponded":[209],"higher":[211],"sensitivity.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}