{"id":"https://openalex.org/W7140161631","doi":"https://doi.org/10.48550/arxiv.2603.21544","title":"Evolutionary Biparty Multiobjective UAV Path Planning: Problems and Empirical Comparisons","display_name":"Evolutionary Biparty Multiobjective UAV Path Planning: Problems and Empirical Comparisons","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140161631","doi":"https://doi.org/10.48550/arxiv.2603.21544"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21544","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21544","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21544","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chen, Kesheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Kesheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Luo, Wenjian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Wenjian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lin, Xin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Song, Zhen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Zhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Chang, Yatong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Yatong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9114000201225281,"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"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9114000201225281,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.028300000354647636,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11489","display_name":"Air Traffic Management and Optimization","score":0.009399999864399433,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.8102999925613403},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.7732999920845032},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5259000062942505},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.5077000260353088},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.45660001039505005},{"id":"https://openalex.org/keywords/artificial-immune-system","display_name":"Artificial immune system","score":0.445499986410141},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4352000057697296}],"concepts":[{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.8102999925613403},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.7732999920845032},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6442000269889832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5873000025749207},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5259000062942505},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C93768804","wikidata":"https://www.wikidata.org/wiki/Q2518735","display_name":"Artificial immune system","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.3312999904155731},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.27619999647140503},{"id":"https://openalex.org/C2988952207","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multiobjective programming","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21544","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21544","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21544","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21544","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8129766583442688,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unmanned":[0],"aerial":[1],"vehicles":[2],"(UAVs)":[3],"have":[4],"been":[5],"widely":[6],"used":[7],"in":[8],"urban":[9],"missions,":[10],"and":[11,35,43,67,71,110,135,149,159,163,171,179,197,207],"proper":[12],"planning":[13,104],"of":[14,25,90],"UAV":[15,102],"paths":[16],"can":[17],"improve":[18],"mission":[19],"efficiency":[20,34,65,109],"while":[21],"reducing":[22],"the":[23,72,88,97,125,130,136,146,156],"risk":[24],"potential":[26],"third-party":[27],"impact.":[28],"Existing":[29],"work":[30],"has":[31],"considered":[32],"all":[33],"safety":[36,69,111],"objectives":[37],"for":[38,96,129,144],"a":[39,47,57,68],"single":[40,58],"decision-maker":[41],"(DM)":[42],"regarded":[44],"this":[45,94],"as":[46,195,203],"multiobjective":[48,101,117,131,139,152,168,174,191,199],"optimization":[49,153],"problem":[50],"(MOP).":[51],"However,":[52],"there":[53],"is":[54,84],"usually":[55],"not":[56],"DM":[59,66],"but":[60],"two":[61],"DMs,":[62],"i.e.,":[63],"an":[64],"DM,":[70],"DMs":[73],"are":[74,113,142,161],"only":[75],"concerned":[76],"with":[77,120,166],"their":[78],"respective":[79],"objectives.":[80],"The":[81,115,181],"final":[82],"decision":[83],"made":[85],"based":[86],"on":[87],"solutions":[89],"both":[91,108],"DMs.":[92],"In":[93],"paper,":[95],"first":[98],"time,":[99],"biparty":[100,151],"path":[103],"(BPMO-UAVPP)":[105],"problems":[106],"involving":[107],"departments":[112],"modeled.":[114],"existing":[116],"immune":[118,132],"algorithm":[119,133,140],"nondominated":[121],"neighbor-based":[122],"selection":[123],"(NNIA),":[124],"hybrid":[126],"evolutionary":[127,169,175,192,200],"framework":[128],"(HEIA),":[134],"adaptive":[137],"immune-inspired":[138],"(AIMA)":[141],"modified":[143],"solving":[145],"BPMO-UAVPP":[147],"problem,":[148],"then":[150],"algorithms,":[154],"including":[155],"BPNNIA,":[157],"BPHEIA,":[158],"BPAIMA,":[160],"proposed":[162],"comprehensively":[164],"compared":[165],"traditional":[167],"algorithms":[170,176,193,201],"typical":[172],"multiparty":[173,198],"(i.e.,":[177],"OptMPNDS":[178],"OptMPNDS2).":[180],"experimental":[182],"results":[183],"show":[184],"that":[185],"BPAIMA":[186],"performs":[187],"better":[188],"than":[189],"ordinary":[190],"such":[194,202],"NSGA-II":[196],"OptMPNDS,":[204],"OptMPNDS2,":[205],"BPNNIA":[206],"BPHEIA.":[208]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-25T00:00:00"}
