{"id":"https://openalex.org/W4411241445","doi":"https://doi.org/10.3390/sym17060934","title":"Optimized Scheduling for Multi-Drop Vehicle\u2013Drone Collaboration with Delivery Constraints Using Large Language Models and Genetic Algorithms with Symmetry Principles","display_name":"Optimized Scheduling for Multi-Drop Vehicle\u2013Drone Collaboration with Delivery Constraints Using Large Language Models and Genetic Algorithms with Symmetry Principles","publication_year":2025,"publication_date":"2025-06-12","ids":{"openalex":"https://openalex.org/W4411241445","doi":"https://doi.org/10.3390/sym17060934"},"language":"en","primary_location":{"id":"doi:10.3390/sym17060934","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17060934","pdf_url":"https://www.mdpi.com/2073-8994/17/6/934/pdf?version=1749721752","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/2073-8994/17/6/934/pdf?version=1749721752","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054383658","display_name":"Mingyang Geng","orcid":"https://orcid.org/0000-0002-7239-1819"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyang Geng","raw_affiliation_strings":["College of Computer Science, National University of Defense Technology, Changsha 410073, China"],"raw_orcid":"https://orcid.org/0000-0002-7239-1819","affiliations":[{"raw_affiliation_string":"College of Computer Science, National University of Defense Technology, Changsha 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100784131","display_name":"Anping Chen","orcid":"https://orcid.org/0000-0003-2085-3863"},"institutions":[{"id":"https://openalex.org/I4210088744","display_name":"Ya'an Polytechnic College","ror":"https://ror.org/00a43vs85","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210088744"]},{"id":"https://openalex.org/I4210165165","display_name":"Anshan Hospital","ror":"https://ror.org/05p2t9n36","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210165165"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Anping Chen","raw_affiliation_strings":["Department of Management Enginearing, Ma\u2019anshan Technical College, Ma\u2019anshan 243000, China","Department of Management Enginearing, Ma'anshan Technical College, Ma'anshan 243000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Management Enginearing, Ma\u2019anshan Technical College, Ma\u2019anshan 243000, China","institution_ids":["https://openalex.org/I4210088744"]},{"raw_affiliation_string":"Department of Management Enginearing, Ma'anshan Technical College, Ma'anshan 243000, China","institution_ids":["https://openalex.org/I4210165165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100784131"],"corresponding_institution_ids":["https://openalex.org/I4210088744","https://openalex.org/I4210165165"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":11.6651,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.97740578,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"17","issue":"6","first_page":"934","last_page":"934"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9904000163078308,"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":0.9812999963760376,"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":0.6988064050674438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6030365824699402},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5616360902786255},{"id":"https://openalex.org/keywords/drop","display_name":"Drop (telecommunication)","score":0.5346391201019287},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4520839750766754},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4491729736328125},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3511159420013428},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3273286819458008},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1774124801158905},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1681811809539795}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.6988064050674438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6030365824699402},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5616360902786255},{"id":"https://openalex.org/C2781345722","wikidata":"https://www.wikidata.org/wiki/Q5308388","display_name":"Drop (telecommunication)","level":2,"score":0.5346391201019287},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4520839750766754},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4491729736328125},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3511159420013428},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3273286819458008},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1774124801158905},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1681811809539795},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/sym17060934","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17060934","pdf_url":"https://www.mdpi.com/2073-8994/17/6/934/pdf?version=1749721752","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/sym17060934","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17060934","pdf_url":"https://www.mdpi.com/2073-8994/17/6/934/pdf?version=1749721752","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/W4411241445.pdf","grobid_xml":"https://content.openalex.org/works/W4411241445.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1977319619","https://openalex.org/W2038411763","https://openalex.org/W2069808690","https://openalex.org/W2144931885","https://openalex.org/W2779455732","https://openalex.org/W2963943323","https://openalex.org/W2972055356","https://openalex.org/W3011794261","https://openalex.org/W3027940156","https://openalex.org/W3111397073","https://openalex.org/W3121897693","https://openalex.org/W3125377832","https://openalex.org/W3147517805","https://openalex.org/W3161165561","https://openalex.org/W3161970973","https://openalex.org/W3197711008","https://openalex.org/W3216846761","https://openalex.org/W4220863497","https://openalex.org/W4283518432","https://openalex.org/W4286321718","https://openalex.org/W4289878177","https://openalex.org/W4293765590","https://openalex.org/W4319081557","https://openalex.org/W4367056173","https://openalex.org/W4391180110","https://openalex.org/W4391558635","https://openalex.org/W4394745253","https://openalex.org/W4400343251","https://openalex.org/W4400582609","https://openalex.org/W4400583089","https://openalex.org/W4403332121","https://openalex.org/W4403659146","https://openalex.org/W4403835060","https://openalex.org/W4407953078","https://openalex.org/W4411113160","https://openalex.org/W6788328305","https://openalex.org/W6793285436","https://openalex.org/W6795768249"],"related_works":["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","https://openalex.org/W2605096541","https://openalex.org/W3200286695","https://openalex.org/W4212885606"],"abstract_inverted_index":{"With":[0],"the":[1,29,98,116,134,176,280],"rapid":[2],"development":[3],"of":[4,90,241,285],"e-commerce":[5],"and":[6,23,31,52,79,85,119,128,136,150,205,214,223,274,282],"globalization,":[7],"logistics":[8,103,157,292],"distribution":[9],"systems":[10],"have":[11],"become":[12],"integral":[13],"to":[14,42,62,76,132,174,188,202,220,268],"modern":[15],"economies,":[16],"directly":[17],"impacting":[18],"transportation":[19],"efficiency,":[20],"resource":[21],"utilization,":[22],"supply":[24],"chain":[25],"flexibility.":[26],"However,":[27],"solving":[28],"Vehicle":[30,135],"Multi-Drone":[32,137],"Cooperative":[33,138],"Delivery":[34,37,139,142],"Problem":[35,140],"with":[36,141,167,249],"Restrictions":[38],"is":[39],"challenging":[40],"due":[41],"complex":[43],"constraints,":[44],"including":[45],"limited":[46],"payloads,":[47],"short":[48],"endurance,":[49],"regional":[50],"restrictions,":[51],"multi-objective":[53],"optimization.":[54],"Traditional":[55],"optimization":[56,73,177,289],"methods,":[57,248,270],"particularly":[58],"genetic":[59,168],"algorithms,":[60],"struggle":[61],"address":[63,133],"these":[64,111],"complexities,":[65],"often":[66],"relying":[67],"on":[68,230],"static":[69],"rules":[70],"or":[71],"single-objective":[72],"that":[74,234],"fails":[75],"balance":[77],"exploration":[78],"exploitation,":[80],"resulting":[81],"in":[82,96,208],"local":[83,216],"optima":[84],"slow":[86],"convergence.":[87],"The":[88,227],"concept":[89],"symmetry":[91,172],"plays":[92],"a":[93,126,156,184,196,215],"crucial":[94],"role":[95],"optimizing":[97],"scheduling":[99,130,158],"process,":[100],"as":[101],"many":[102],"problems":[104],"inherently":[105],"possess":[106],"symmetrical":[107],"properties.":[108],"By":[109],"exploiting":[110],"symmetries,":[112],"we":[113,154],"can":[114],"reduce":[115],"problem\u2019s":[117],"complexity":[118],"improve":[120,224],"solution":[121,225],"efficiency.":[122],"This":[123],"study":[124],"proposes":[125],"novel":[127],"scalable":[129],"approach":[131],"Restrictions,":[143],"tackling":[144],"its":[145],"high":[146],"complexity,":[147],"constraint":[148],"handling,":[149],"real-world":[151,283],"applicability.":[152,276],"Specifically,":[153],"propose":[155],"method":[159],"called":[160],"Loegised,":[161],"which":[162],"integrates":[163],"large":[164],"language":[165,287],"models":[166],"algorithms":[169],"while":[170],"incorporating":[171],"principles":[173],"enhance":[175],"process.":[178],"Loegised":[179,235,260],"includes":[180],"three":[181],"innovative":[182],"modules:":[183],"cognitive":[185],"initialization":[186],"module":[187,201],"accelerate":[189],"convergence":[190],"by":[191,252,264],"generating":[192],"high-quality":[193],"initial":[194],"solutions,":[195],"dynamic":[197],"operator":[198],"parameter":[199],"adjustment":[200],"optimize":[203],"crossover":[204],"mutation":[206],"rates":[207],"real-time":[209],"for":[210,290],"better":[211],"global":[212],"search,":[213],"optimum":[217],"escape":[218],"mechanism":[219],"prevent":[221],"stagnation":[222],"diversity.":[226],"experimental":[228],"results":[229],"benchmark":[231],"datasets":[232],"show":[233],"achieves":[236],"an":[237],"average":[238],"delivery":[239,262],"time":[240,263],"14.80,":[242],"significantly":[243],"outperforming":[244],"six":[245],"state-of-the-art":[246],"baseline":[247],"improvements":[250],"confirmed":[251],"Wilcoxon":[253],"signed-rank":[254],"tests":[255],"(p&lt;0.001).":[256],"In":[257],"large-scale":[258],"scenarios,":[259],"reduces":[261],"over":[265],"20%":[266],"compared":[267],"conventional":[269],"demonstrating":[271],"strong":[272],"scalability":[273],"practical":[275],"These":[277],"findings":[278],"validate":[279],"effectiveness":[281],"potential":[284],"symmetry-enhanced,":[286],"model-guided":[288],"advanced":[291],"scheduling.":[293]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-12T08:23:45.883708","created_date":"2025-10-10T00:00:00"}
