{"id":"https://openalex.org/W7225658283","doi":"https://doi.org/10.1007/s44196-026-01684-3","title":"An Adaptive Dual-Leader Optimization Framework with Elite Stratification for Global Optimization and Automatic Clustering","display_name":"An Adaptive Dual-Leader Optimization Framework with Elite Stratification for Global Optimization and Automatic Clustering","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225658283","doi":"https://doi.org/10.1007/s44196-026-01684-3"},"language":"en","primary_location":{"id":"doi:10.1007/s44196-026-01684-3","doi":"https://doi.org/10.1007/s44196-026-01684-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44196-026-01684-3","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44196-026-01684-3","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103145679","display_name":"Subrat Kumar Nayak","orcid":"https://orcid.org/0000-0002-7438-9085","observed_orcids":["https://orcid.org/0000-0002-7438-9085","https://orcid.org/0000-0002-9832-514X"]},"institutions":[{"id":"https://openalex.org/I193073490","display_name":"Siksha O Anusandhan University","ror":"https://ror.org/056ep7w45","country_code":"IN","type":"education","lineage":["https://openalex.org/I193073490"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subrat Kumar Nayak","raw_affiliation_strings":["Computer Science and Engineering Department, ITER, Siksh\u00e0O\u2019Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, ITER, Siksh\u00e0O\u2019Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India","institution_ids":["https://openalex.org/I193073490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054835450","display_name":"Biswa Ranjan Senapati","orcid":"https://orcid.org/0000-0001-8975-2812","observed_orcids":["https://orcid.org/0000-0001-8975-2812"]},"institutions":[{"id":"https://openalex.org/I193073490","display_name":"Siksha O Anusandhan University","ror":"https://ror.org/056ep7w45","country_code":"IN","type":"education","lineage":["https://openalex.org/I193073490"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Biswa Ranjan Senapati","raw_affiliation_strings":["Computer Science and Engineering Department, ITER, Siksh\u00e0O\u2019Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, ITER, Siksh\u00e0O\u2019Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India","institution_ids":["https://openalex.org/I193073490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009670711","display_name":"Tribhuvan Singh","orcid":"https://orcid.org/0000-0002-0872-6987","observed_orcids":["https://orcid.org/0000-0002-0872-6987"]},"institutions":[{"id":"https://openalex.org/I193073490","display_name":"Siksha O Anusandhan University","ror":"https://ror.org/056ep7w45","country_code":"IN","type":"education","lineage":["https://openalex.org/I193073490"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Tribhuvan Singh","raw_affiliation_strings":["Computer Science and Engineering Department, ITER, Siksh\u00e0O\u2019Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, ITER, Siksh\u00e0O\u2019Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India","institution_ids":["https://openalex.org/I193073490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5009670711"],"corresponding_institution_ids":["https://openalex.org/I193073490"],"apc_list":{"value":2490,"currency":"USD","value_usd":2490},"apc_paid":{"value":2490,"currency":"USD","value_usd":2490},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":1.0,"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/T11946","display_name":"Antenna Design and Optimization","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11195","display_name":"Simulation Techniques and Applications","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploration-exploitation-trade-off","display_name":"exploration-exploitation balance","score":0.9269999861717224},{"id":"https://openalex.org/keywords/metaheuristic-optimization","display_name":"metaheuristic optimization","score":0.746999979019165},{"id":"https://openalex.org/keywords/high-dimensional-optimization","display_name":"high-dimensional optimization","score":0.6740000247955322},{"id":"https://openalex.org/keywords/cec2017-benchmark-functions","display_name":"CEC2017 benchmark functions","score":0.8130000233650208},{"id":"https://openalex.org/keywords/automatic-clustering","display_name":"automatic clustering","score":0.6779999732971191},{"id":"https://openalex.org/keywords/swarm-intelligence","display_name":"swarm intelligence","score":0.7020000219345093},{"id":"https://openalex.org/keywords/global-optimization","display_name":"global optimization","score":0.3310000002384186}],"concepts":[{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.6104999780654907},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5921000242233276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.582099974155426},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5745999813079834},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5631999969482422},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5085999965667725},{"id":"https://openalex.org/C151552104","wikidata":"https://www.wikidata.org/wiki/Q7705809","display_name":"Test suite","level":4,"score":0.48260000348091125},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.39100000262260437},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3463999927043915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32409998774528503},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C181335050","wikidata":"https://www.wikidata.org/wiki/Q14915018","display_name":"Swarm behaviour","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29260000586509705},{"id":"https://openalex.org/C141934464","wikidata":"https://www.wikidata.org/wiki/Q3305386","display_name":"Local optimum","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27410000562667847},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.26649999618530273}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s44196-026-01684-3","doi":"https://doi.org/10.1007/s44196-026-01684-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44196-026-01684-3","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s44196-026-01684-3","doi":"https://doi.org/10.1007/s44196-026-01684-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44196-026-01684-3","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7128048385","https://openalex.org/W2053432776","https://openalex.org/W2365929242","https://openalex.org/W2355496386","https://openalex.org/W4387444355","https://openalex.org/W7161756215","https://openalex.org/W7126164948","https://openalex.org/W2966569580","https://openalex.org/W4317459848","https://openalex.org/W4223424642"],"abstract_inverted_index":{"Metaheuristic":[0],"algorithms":[1,340],"face":[2],"three":[3,50,262],"common":[4],"problems.":[5],"It":[6,39,87,232,264,328],"is":[7,40,57,84,109,154,233,265,294,307,320,349,367],"hard":[8],"to":[9,52,90,236,316],"balance":[10],"exploration":[11,92],"and":[12,48,99,127,170,198,210,224,239,244,285,300,311,336,355,373],"exploitation.":[13],"Search":[14],"can":[15],"converge":[16],"too":[17],"early.":[18],"Performance":[19],"often":[20],"drops":[21],"as":[22],"the":[23,30,43,65,91,95,100,124,162,183,214,249,253,333,344],"dimension":[24],"grows.":[25],"This":[26],"paper":[27],"proposes":[28],"EG-APS-DLPOA,":[29],"Elite-Guided":[31],"Adaptive":[32],"Phase":[33],"Switching":[34],"Dual-Leader":[35],"Piranha":[36,44],"Optimisation":[37,45],"Algorithm.":[38],"built":[41],"on":[42,156,206,297,323],"Algorithm":[46],"(POA)":[47],"adds":[49,88,146],"mechanisms":[51],"it.":[53],"The":[54,82,106,112,152,178,318,364],"first":[55,219,259],"mechanism":[56,135],"adaptive":[58],"phase":[59],"switching.":[60],"A":[61],"decaying":[62],"probability":[63],"controls":[64],"search.":[66],"Early":[67],"iterations":[68,74],"favour":[69,75],"broad":[70],"exploration,":[71],"while":[72],"later":[73],"focused":[76],"exploitation,":[77],"with":[78,309,332],"no":[79],"fixed":[80],"schedule.":[81],"second":[83,225,330],"dual-leader":[85],"guidance.":[86],"direction":[89],"step,":[93],"using":[94],"global":[96,125],"best":[97,126,334],"position":[98,102],"mean":[101],"of":[103,115,248,270,279,338,346],"elite":[104,347],"agents.":[105],"third":[107],"one":[108,147],"elite-agent":[110],"stratification.":[111],"top":[113],"20%":[114],"agents":[116,121],"are":[117],"marked":[118],"elite.":[119],"Elite":[120],"always":[122],"exploit":[123],"never":[128],"explore.":[129],"An":[130],"ablation":[131,242],"study":[132],"tests":[133],"each":[134,205],"alone,":[136],"in":[137],"order:":[138],"POA,":[139],"DL-POA,":[140],"APS-DLPOA,":[141],"then":[142],"EG-APS-DLPOA.":[143],"Each":[144],"step":[145],"mechanism,":[148],"isolating":[149],"its":[150,240],"effect.":[151],"algorithm":[153,319],"tested":[155,165,322,368],"38":[157],"benchmark":[158],"functions.":[159,212,251],"Eighteen":[160],"form":[161],"main":[163],"suite,":[164,185,216],"at":[166,191,220,228,260,273,281,288,351,360,369],"D":[167,171,192,195,199,221,229,274,282,289,352,356,361,370,374],"=":[168,172,193,196,200,222,230,275,283,290,353,357,362,371,375],"30":[169,175,203,223,276,372],"50":[173,197,284,354,376],"over":[174,202],"runs":[176,204],"each.":[177],"other":[179],"20":[180],"come":[181],"from":[182],"CEC2017":[184,254],"giving":[186],"an":[187],"independent":[188],"validation":[189],"test":[190],"30,":[194],"100,":[201],"harder,":[207],"shifted,":[208],"rotated,":[209,298],"hybrid":[211,301],"On":[213,252,303,342],"classical":[215,365],"EG-APS-DLPOA":[217,257],"ranks":[218,258,329],"behind":[226],"WOA":[227,245,310],"50.":[231],"statistically":[234],"equivalent":[235],"WOA,":[237],"GWO":[238],"own":[241],"variants,":[243],"wins":[246],"most":[247],"separable":[250,304],"suite":[255,366],",":[256,277],"all":[261,286,339],"dimensions.":[263],"significantly":[266],"better":[267],"than":[268,359],"8":[269],"10":[271,280,287],"competitors":[272],"9":[278],"100.":[291],"Its":[292],"advantage":[293],"therefore":[295],"clearest":[296],"non-separable":[299],"landscapes.":[302],"functions,":[305],"it":[306],"competitive":[308],"GWO,":[312],"but":[313],"not":[314],"superior":[315],"them.":[317],"also":[321],"11":[324],"UCI":[325],"clustering":[326],"datasets.":[327],"overall,":[331],"Accuracy":[335],"ARI":[337],"tested.":[341],"CEC2017,":[343],"benefit":[345],"stratification":[348],"larger":[350],"100":[358],"30.":[363],"only.":[377]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}
