{"id":"https://openalex.org/W2153635215","doi":"https://doi.org/10.1109/cec.2003.1299903","title":"DAFHEA: a dynamic approximate fitness-based hybrid EA for optimisation problems","display_name":"DAFHEA: a dynamic approximate fitness-based hybrid EA for optimisation problems","publication_year":2004,"publication_date":"2004-07-09","ids":{"openalex":"https://openalex.org/W2153635215","doi":"https://doi.org/10.1109/cec.2003.1299903","mag":"2153635215"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2003.1299903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2003.1299903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2003 Congress on Evolutionary Computation, 2003. CEC '03.","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchoutput.csu.edu.au/en/publications/ef1224e3-26cb-473b-8eb0-fd99d3aa3aba","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075844123","display_name":"Maumita Bhattacharya","orcid":"https://orcid.org/0000-0002-5276-1421"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"M. Bhattacharya","raw_affiliation_strings":["Gippsland School of Computing and Information Technology, Monash University, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Gippsland School of Computing and Information Technology, Monash University, VIC, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053408745","display_name":"Guojun Lu","orcid":"https://orcid.org/0000-0003-2523-7576"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guojun Lu","raw_affiliation_strings":["Gippsland School of Computing and Information Technology, Monash University, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Gippsland School of Computing and Information Technology, Monash University, VIC, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075844123"],"corresponding_institution_ids":["https://openalex.org/I56590836"],"apc_list":null,"apc_paid":null,"fwci":1.8709,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.88425527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"1879","last_page":"1886"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9995999932289124,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9995999932289124,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9994999766349792,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.7984384298324585},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6942676305770874},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.614257276058197},{"id":"https://openalex.org/keywords/fitness-approximation","display_name":"Fitness approximation","score":0.6122768521308899},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5404660701751709},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5242019891738892},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5038956999778748},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4421737492084503},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.3939898610115051},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3128969073295593},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21716222167015076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1624164879322052}],"concepts":[{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.7984384298324585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6942676305770874},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.614257276058197},{"id":"https://openalex.org/C148392497","wikidata":"https://www.wikidata.org/wiki/Q16250539","display_name":"Fitness approximation","level":4,"score":0.6122768521308899},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5404660701751709},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5242019891738892},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5038956999778748},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4421737492084503},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3939898610115051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3128969073295593},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21716222167015076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1624164879322052},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cec.2003.1299903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2003.1299903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2003 Congress on Evolutionary Computation, 2003. CEC '03.","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/ef1224e3-26cb-473b-8eb0-fd99d3aa3aba","is_oa":true,"landing_page_url":"https://researchoutput.csu.edu.au/en/publications/ef1224e3-26cb-473b-8eb0-fd99d3aa3aba","pdf_url":null,"source":{"id":"https://openalex.org/S7407055442","display_name":"Charles Sturt University Research Output (CRO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Bhattacharya, M & Lu, G 2003, DAFHEA : A Dynamic Approximate Fitness based Hybrid Evolutionary Algorithm for optimisation problems. in IEEE Congress on Evolutionary Computation 2003 (CEC 2003). vol. 3, IEEE Press, USA, pp. 1879-1886, IEEE Congress on Evolutionary Computation, Australia, 08/12/03. https://doi.org/10.1109/CEC.2003.1299903","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/ef1224e3-26cb-473b-8eb0-fd99d3aa3aba","is_oa":true,"landing_page_url":"https://researchoutput.csu.edu.au/en/publications/ef1224e3-26cb-473b-8eb0-fd99d3aa3aba","pdf_url":null,"source":{"id":"https://openalex.org/S7407055442","display_name":"Charles Sturt University Research Output (CRO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Bhattacharya, M & Lu, G 2003, DAFHEA : A Dynamic Approximate Fitness based Hybrid Evolutionary Algorithm for optimisation problems. in IEEE Congress on Evolutionary Computation 2003 (CEC 2003). vol. 3, IEEE Press, USA, pp. 1879-1886, IEEE Congress on Evolutionary Computation, Australia, 08/12/03. https://doi.org/10.1109/CEC.2003.1299903","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1507016871","https://openalex.org/W1532738248","https://openalex.org/W1554663460","https://openalex.org/W1554944419","https://openalex.org/W1591022951","https://openalex.org/W1869391892","https://openalex.org/W1939479690","https://openalex.org/W1964357740","https://openalex.org/W1981388088","https://openalex.org/W2012451526","https://openalex.org/W2018044188","https://openalex.org/W2041397719","https://openalex.org/W2045933457","https://openalex.org/W2103507771","https://openalex.org/W2156909104","https://openalex.org/W2166739626","https://openalex.org/W2171033594","https://openalex.org/W2519881875","https://openalex.org/W4285719527","https://openalex.org/W4388297464","https://openalex.org/W6640484103"],"related_works":["https://openalex.org/W1622672652","https://openalex.org/W2159937791","https://openalex.org/W2017545286","https://openalex.org/W2164084664","https://openalex.org/W1995719995","https://openalex.org/W4299643771","https://openalex.org/W2951823782","https://openalex.org/W1606502848","https://openalex.org/W2489890244","https://openalex.org/W2550292406"],"abstract_inverted_index":{"A":[0,22],"dynamic":[1],"approximate":[2,20],"fitness-based":[3],"hybrid":[4],"evolutionary":[5],"algorithm":[6],"is":[7,27,64],"presented":[8],"here.":[9],"The":[10],"proposed":[11,77],"model":[12,59],"partially":[13],"replaces":[14],"expensive":[15,34,44],"fitness":[16],"evaluation":[17,36,46],"by":[18],"an":[19],"model.":[21,42],"cluster-based":[23],"intelligent":[24],"guided":[25],"technique":[26],"used":[28],"to":[29,66],"decide":[30],"on":[31],"use":[32],"of":[33,48,75],"function":[35,45],"and":[37],"dynamically":[38],"adapt":[39],"the":[40,49,57,72,76],"predicted":[41,58],"Avoiding":[43],"speeds":[47],"optimisation":[50],"process.":[51],"Also":[52],"additional":[53],"information":[54],"derived":[55],"from":[56],"at":[60],"lower":[61],"computational":[62],"expense,":[63],"exploited":[65],"improve":[67],"solution.":[68],"Experimental":[69],"findings":[70],"support":[71],"theoretical":[73],"basis":[74],"framework.":[78]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}
