{"id":"https://openalex.org/W4385189126","doi":"https://doi.org/10.1145/3583133.3590640","title":"Multi-Surrogate Assisted PSO with Multiple Exemplars for Expensive Multimodal Multi-Objective Optimization","display_name":"Multi-Surrogate Assisted PSO with Multiple Exemplars for Expensive Multimodal Multi-Objective Optimization","publication_year":2023,"publication_date":"2023-07-15","ids":{"openalex":"https://openalex.org/W4385189126","doi":"https://doi.org/10.1145/3583133.3590640"},"language":"en","primary_location":{"id":"doi:10.1145/3583133.3590640","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583133.3590640","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029270853","display_name":"Zhiming Lv","orcid":"https://orcid.org/0000-0002-5834-2025"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiming Lv","raw_affiliation_strings":["Northwest A&amp;F University, Yangling, China"],"raw_orcid":"https://orcid.org/0000-0002-5834-2025","affiliations":[{"raw_affiliation_string":"Northwest A&amp;F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086155428","display_name":"Shuqin Li","orcid":"https://orcid.org/0000-0002-5079-8618"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqin Li","raw_affiliation_strings":["Northwest A&amp;F University, Yangling, China"],"raw_orcid":"https://orcid.org/0000-0002-5079-8618","affiliations":[{"raw_affiliation_string":"Northwest A&amp;F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038328022","display_name":"Hongguang Sun","orcid":"https://orcid.org/0000-0003-4359-6644"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongguang Sun","raw_affiliation_strings":["Northwest A&amp;F University, Yangling, China"],"raw_orcid":"https://orcid.org/0000-0003-4359-6644","affiliations":[{"raw_affiliation_string":"Northwest A&amp;F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445041","display_name":"Hongming Zhang","orcid":"https://orcid.org/0000-0003-4605-8577"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongming Zhang","raw_affiliation_strings":["Northwest A&amp;F University, Yangling, China"],"raw_orcid":"https://orcid.org/0000-0003-4605-8577","affiliations":[{"raw_affiliation_string":"Northwest A&amp;F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I89652312"],"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":"387","last_page":"390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9659000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7093161344528198},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6760733127593994},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6604493856430054},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.6396610736846924},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.590136706829071},{"id":"https://openalex.org/keywords/multi-swarm-optimization","display_name":"Multi-swarm optimization","score":0.5742369294166565},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.5492071509361267},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.508611798286438},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.49127262830734253},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.48434245586395264},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48017874360084534},{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.4770768880844116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44042885303497314},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4126521944999695},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20108449459075928},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20057126879692078}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7093161344528198},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6760733127593994},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6604493856430054},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.6396610736846924},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.590136706829071},{"id":"https://openalex.org/C122357587","wikidata":"https://www.wikidata.org/wiki/Q6934508","display_name":"Multi-swarm optimization","level":3,"score":0.5742369294166565},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.5492071509361267},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.508611798286438},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.49127262830734253},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.48434245586395264},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48017874360084534},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.4770768880844116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44042885303497314},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4126521944999695},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20108449459075928},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20057126879692078},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583133.3590640","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583133.3590640","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5099999904632568,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G7855469574","display_name":null,"funder_award_id":"62203366","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2558610617","https://openalex.org/W2758008099","https://openalex.org/W2808442772","https://openalex.org/W2899519149","https://openalex.org/W2933150416","https://openalex.org/W2947137854","https://openalex.org/W2981587540","https://openalex.org/W3043065261","https://openalex.org/W3154887145","https://openalex.org/W3160947956"],"related_works":["https://openalex.org/W2161494499","https://openalex.org/W2911636622","https://openalex.org/W2906115061","https://openalex.org/W2977596624","https://openalex.org/W3103120015","https://openalex.org/W2145877535","https://openalex.org/W2744730182","https://openalex.org/W3134440233","https://openalex.org/W2751605210","https://openalex.org/W2207859038"],"abstract_inverted_index":{"Expensive":[0],"multimodal":[1],"multi-objective":[2],"problems":[3],"widely":[4],"exit":[5],"in":[6,9,108,141],"real-world":[7],"applications,":[8],"which":[10],"multiple":[11,64,91,106],"Pareto":[12,33],"solutions":[13],"correspond":[14],"to":[15,77,136,158],"the":[16,22,36,50,79,103,109,112,119,122,138,142,152],"same":[17],"objective":[18,145],"values.":[19],"To":[20],"tackle":[21],"above-mentioned":[23],"problems,":[24],"traditional":[25],"particle":[26,60,99],"swarm":[27,61],"optimization":[28,62,87,101],"algorithms":[29,162],"always":[30],"select":[31],"a":[32,57,69,84],"solution":[34],"from":[35],"archive":[37,127],"based":[38,72,89,117,130],"on":[39,73,90,118,131,163],"preferences":[40],"as":[41],"an":[42,126],"exemplar.":[43],"However,":[44],"this":[45,96],"exemplar":[46,52,114],"may":[47],"not":[48],"be":[49],"best":[51],"for":[53],"each":[54,98],"particle.":[55],"Therefore,":[56],"multi-surrogate":[58,70],"assisted":[59,86],"with":[63],"exemplars":[65,92,107],"is":[66,75,93,115,134,155],"proposed.":[67],"Firstly,":[68],"model":[71],"clustering":[74],"constructed":[76],"fit":[78],"many-to-one":[80],"mapping":[81],"relationship.":[82],"Secondly,":[83],"surrogate":[85,123],"strategy":[88,129],"developed.":[94],"In":[95],"strategy,":[97],"performs":[100],"under":[102],"guidance":[104],"of":[105,121],"archive,":[110],"and":[111,144],"optimal":[113],"selected":[116],"evaluations":[120],"models.":[124],"Finally,":[125],"update":[128],"crowding":[132],"distance":[133],"proposed":[135,153],"balance":[137],"diversity":[139],"both":[140],"decision":[143],"spaces.":[146],"The":[147],"experimental":[148],"results":[149],"show":[150],"that":[151],"algorithm":[154],"significantly":[156],"superior":[157],"eight":[159],"state-of-the-art":[160],"evolutionary":[161],"chosen":[164],"benchmark":[165],"problems.":[166]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
