{"id":"https://openalex.org/W2786725723","doi":"https://doi.org/10.1109/ssci.2017.8285235","title":"Particle swarm optimization with a modified learning strategy and blending crossover","display_name":"Particle swarm optimization with a modified learning strategy and blending crossover","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2786725723","doi":"https://doi.org/10.1109/ssci.2017.8285235","mag":"2786725723"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2017.8285235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8285235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5047241166","display_name":"Aditya Prasad Panda","orcid":null},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aditya Panda","raw_affiliation_strings":["ETCE Department, Jadavpur University, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETCE Department, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043565079","display_name":"Rammohan Mallipeddi","orcid":"https://orcid.org/0000-0001-9071-1145"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Rammohan Mallipeddi","raw_affiliation_strings":["Kyungpook National University, Daegu, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000078546","display_name":"Swagatam Das","orcid":"https://orcid.org/0000-0001-6843-4508"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swagatam Das","raw_affiliation_strings":["Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9998999834060669,"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":0.9998999834060669,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9860000014305115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.8531445264816284},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.755073070526123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5642926096916199},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.44632431864738464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26422709226608276},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1804516613483429},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.136803537607193}],"concepts":[{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.8531445264816284},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.755073070526123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5642926096916199},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44632431864738464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26422709226608276},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1804516613483429},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.136803537607193}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci.2017.8285235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8285235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W31462882","https://openalex.org/W1120240326","https://openalex.org/W1179686678","https://openalex.org/W1539307555","https://openalex.org/W1545960569","https://openalex.org/W1546627672","https://openalex.org/W1565902586","https://openalex.org/W1796315384","https://openalex.org/W1911731270","https://openalex.org/W1987234899","https://openalex.org/W1998391576","https://openalex.org/W2069099024","https://openalex.org/W2108388069","https://openalex.org/W2116850883","https://openalex.org/W2118840131","https://openalex.org/W2131613989","https://openalex.org/W2139339670","https://openalex.org/W2152195021","https://openalex.org/W2165299997","https://openalex.org/W2169245194","https://openalex.org/W2187537484","https://openalex.org/W2259657469","https://openalex.org/W2317744239","https://openalex.org/W2558227003","https://openalex.org/W2917884856","https://openalex.org/W6699831583","https://openalex.org/W6759768743"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2347477706","https://openalex.org/W4299389082","https://openalex.org/W1943663474","https://openalex.org/W2306830238","https://openalex.org/W2110294633","https://openalex.org/W1829715381","https://openalex.org/W1978349322","https://openalex.org/W2962747841","https://openalex.org/W2014162767"],"abstract_inverted_index":{"Particle":[0],"Swarm":[1],"Optimization":[2],"(PSO)":[3],"is":[4,31,110,138],"a":[5,59,64,78],"simple":[6],"yet":[7],"elegant":[8],"derivative-free":[9],"algorithm":[10],"for":[11,100],"solving":[12],"continuous,":[13],"multi-modal,":[14],"non-convex":[15],"and":[16,97,128,173],"multi-dimensional":[17],"optimization":[18],"problems":[19],"of":[20,42,52,89,123,132,145,167,171],"widely":[21],"different":[22],"nature.":[23],"However,":[24],"one":[25],"concern":[26],"about":[27],"the":[28,53,107,114,124,135,146,165],"conventional":[29],"PSO":[30,55,115],"that,":[32],"it":[33],"suffers":[34],"from":[35,86],"premature":[36],"convergence,":[37],"due":[38],"to":[39,68,117],"quick":[40],"loss":[41],"diversity.":[43],"In":[44],"this":[45,70],"paper,":[46],"we":[47],"propose":[48],"an":[49],"improvised":[50],"version":[51],"standard":[54,142],"(PSO-ML),":[56],"which":[57],"integrates":[58],"novel":[60,74],"learning":[61,75,85],"strategy":[62,76],"with":[63,113],"genetic":[65,104],"crossover":[66,105,109],"scheme":[67],"circumvent":[69],"limitation.":[71],"The":[72,154],"suggested":[73],"generates":[77],"single":[79],"robust":[80],"exemplar":[81],"vector":[82],"by":[83],"dynamically":[84],"individual":[87],"dimensions":[88],"three":[90],"guiding":[91],"solutions:":[92],"personal":[93],"best,":[94,96],"global":[95],"local":[98],"best":[99],"each":[101,130],"particle.":[102],"A":[103],"scheme,":[106],"blending":[108],"also":[111],"integrated":[112],"model,":[116],"enhance":[118],"exploration":[119],"through":[120],"rapid":[121],"search":[122],"function":[125],"space":[126],"between":[127],"around":[129],"pair":[131],"particles":[133],"in":[134,169],"swarm.":[136],"PSO-ML":[137,168],"tested":[139],"on":[140,150],"25":[141],"benchmark":[143],"functions":[144],"IEEE":[147],"CEC":[148],"(Congress":[149],"Evolutionary":[151],"Computation)":[152],"2013.":[153],"results":[155],"are":[156],"then":[157],"compared":[158],"against":[159],"other":[160],"state-of-the-art":[161],"algorithms,":[162],"thus":[163],"illustrating":[164],"advantages":[166],"terms":[170],"accuracy":[172],"computational":[174],"cost.":[175]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}