{"id":"https://openalex.org/W2590464326","doi":"https://doi.org/10.1109/icci-cc.2016.7862030","title":"An information theoretic criterion for adaptive multiobjective memetic optimization","display_name":"An information theoretic criterion for adaptive multiobjective memetic optimization","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2590464326","doi":"https://doi.org/10.1109/icci-cc.2016.7862030","mag":"2590464326"},"language":"en","primary_location":{"id":"doi:10.1109/icci-cc.2016.7862030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"},"type":"article","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/A5060952836","display_name":"Hieu V. Dang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hieu V. Dang","raw_affiliation_strings":["Sightline Innovation Inc., Winnipeg, Canada"],"affiliations":[{"raw_affiliation_string":"Sightline Innovation Inc., Winnipeg, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038834884","display_name":"Witold Kinsner","orcid":"https://orcid.org/0000-0002-6759-1410"},"institutions":[{"id":"https://openalex.org/I46247651","display_name":"University of Manitoba","ror":"https://ror.org/02gfys938","country_code":"CA","type":"education","lineage":["https://openalex.org/I46247651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Witold Kinsner","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada","institution_ids":["https://openalex.org/I46247651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060952836"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7306,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77339078,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"9","issue":null,"first_page":"15","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9969000220298767,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/memetics","display_name":"Memetics","score":0.7643800973892212},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.7008296251296997},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.6702660322189331},{"id":"https://openalex.org/keywords/memetic-algorithm","display_name":"Memetic algorithm","score":0.6675440073013306},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.6530095338821411},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6454931497573853},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5602965950965881},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5333874821662903},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.49401289224624634},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47143855690956116},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4705667197704315},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4553963243961334},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.4446495473384857},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3552626967430115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2851376533508301}],"concepts":[{"id":"https://openalex.org/C51620047","wikidata":"https://www.wikidata.org/wiki/Q23399","display_name":"Memetics","level":2,"score":0.7643800973892212},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.7008296251296997},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.6702660322189331},{"id":"https://openalex.org/C35129592","wikidata":"https://www.wikidata.org/wiki/Q324793","display_name":"Memetic algorithm","level":3,"score":0.6675440073013306},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.6530095338821411},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6454931497573853},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5602965950965881},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5333874821662903},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.49401289224624634},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47143855690956116},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4705667197704315},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4553963243961334},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.4446495473384857},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3552626967430115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2851376533508301},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icci-cc.2016.7862030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W18216792","https://openalex.org/W74508158","https://openalex.org/W225560312","https://openalex.org/W1519778441","https://openalex.org/W1595498733","https://openalex.org/W1846834309","https://openalex.org/W1972780579","https://openalex.org/W1980750007","https://openalex.org/W1985613492","https://openalex.org/W1987958230","https://openalex.org/W1990368529","https://openalex.org/W1995263179","https://openalex.org/W1995714897","https://openalex.org/W2008434012","https://openalex.org/W2016384789","https://openalex.org/W2037640238","https://openalex.org/W2045955107","https://openalex.org/W2055025427","https://openalex.org/W2081101117","https://openalex.org/W2091911904","https://openalex.org/W2095174646","https://openalex.org/W2104274529","https://openalex.org/W2110843745","https://openalex.org/W2113076747","https://openalex.org/W2125899728","https://openalex.org/W2126105956","https://openalex.org/W2143185749","https://openalex.org/W2155345556","https://openalex.org/W2162590226","https://openalex.org/W2170186790","https://openalex.org/W4220690171","https://openalex.org/W4292864963","https://openalex.org/W6608886761","https://openalex.org/W6809513477"],"related_works":["https://openalex.org/W2056356393","https://openalex.org/W2904131175","https://openalex.org/W115040951","https://openalex.org/W4242383018","https://openalex.org/W2077418700","https://openalex.org/W2102350580","https://openalex.org/W2008607212","https://openalex.org/W2095089069","https://openalex.org/W4211189042","https://openalex.org/W2787833928"],"abstract_inverted_index":{"Multiobjective":[0],"memetic":[1,111],"optimization":[2,11,54,112],"algorithms":[3,58,113],"(MMOAs)":[4],"are":[5],"recently":[6],"applied":[7,120],"to":[8,24,30,41,95,121],"solve":[9],"nonlinear":[10],"problems":[12,125],"with":[13,126],"conflicting":[14],"objectives.":[15],"An":[16],"important":[17],"issue":[18],"in":[19,52,105],"an":[20,84],"MMOA":[21],"is":[22,119],"how":[23],"identify":[25],"the":[26,43,49,61,65,74,90,97],"relative":[27,44,92],"best":[28],"solutions":[29,47],"guide":[31,96],"its":[32,70],"adaptive":[33,98,109],"processes.":[34],"Pareto":[35,66],"dominance":[36,67],"has":[37],"been":[38],"used":[39],"extensively":[40],"find":[42],"relations":[45],"between":[46],"for":[48],"fitness":[50],"assessment":[51],"multiobjective":[53,110],"based":[55,63,88],"on":[56,64,89],"evolutionary":[57],"(MOEA).":[59],"However,":[60],"approach":[62],"criterion":[68,87],"decreases":[69],"convergence":[71],"speed":[72],"when":[73],"number":[75],"of":[76,108,117],"objectives":[77],"increases.":[78],"In":[79],"this":[80],"paper,":[81],"we":[82],"propose":[83],"effective":[85],"information-theoretic":[86],"multiscale":[91],"R\u00e9nyi":[93],"entropy":[94],"selection,":[99],"clustering,":[100],"and":[101],"local":[102],"learning":[103],"processes":[104],"our":[106],"framework":[107],"(AMMOA).":[114],"The":[115],"implementation":[116],"AMMOA":[118],"several":[122],"benchmark":[123],"test":[124],"remarkable":[127],"results.":[128]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
