{"id":"https://openalex.org/W4294811652","doi":"https://doi.org/10.1109/cec55065.2022.9870231","title":"Automated Design of Hybrid Metaheuristics: A Fitness Landscape Analysis","display_name":"Automated Design of Hybrid Metaheuristics: A Fitness Landscape Analysis","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4294811652","doi":"https://doi.org/10.1109/cec55065.2022.9870231"},"language":"en","primary_location":{"id":"doi:10.1109/cec55065.2022.9870231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec55065.2022.9870231","pdf_url":null,"source":{"id":"https://openalex.org/S4363605353","display_name":"2022 IEEE Congress on Evolutionary Computation (CEC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Congress on Evolutionary Computation (CEC)","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/A5024558233","display_name":"Ahmed Nazar Hassan","orcid":"https://orcid.org/0000-0003-4475-5993"},"institutions":[{"id":"https://openalex.org/I69552723","display_name":"University of Pretoria","ror":"https://ror.org/00g0p6g84","country_code":"ZA","type":"education","lineage":["https://openalex.org/I69552723"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Ahmed Hassan","raw_affiliation_strings":["University of Pretoria,Department of Computer Science,Pretoria,South Africa","Department of Computer Science, University of Pretoria, Pretoria, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pretoria,Department of Computer Science,Pretoria,South Africa","institution_ids":["https://openalex.org/I69552723"]},{"raw_affiliation_string":"Department of Computer Science, University of Pretoria, Pretoria, South Africa","institution_ids":["https://openalex.org/I69552723"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060039893","display_name":"Nelishia Pillay","orcid":"https://orcid.org/0000-0003-3902-5582"},"institutions":[{"id":"https://openalex.org/I69552723","display_name":"University of Pretoria","ror":"https://ror.org/00g0p6g84","country_code":"ZA","type":"education","lineage":["https://openalex.org/I69552723"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Nelishia Pillay","raw_affiliation_strings":["University of Pretoria,Department of Computer Science,Pretoria,South Africa","Department of Computer Science, University of Pretoria, Pretoria, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pretoria,Department of Computer Science,Pretoria,South Africa","institution_ids":["https://openalex.org/I69552723"]},{"raw_affiliation_string":"Department of Computer Science, University of Pretoria, Pretoria, South Africa","institution_ids":["https://openalex.org/I69552723"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I69552723"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"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/T12176","display_name":"Optimization and Packing Problems","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12176","display_name":"Optimization and Packing Problems","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12288","display_name":"Optimization and Search Problems","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/metaheuristic","display_name":"Metaheuristic","score":0.8521329164505005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6823990345001221},{"id":"https://openalex.org/keywords/fitness-landscape","display_name":"Fitness landscape","score":0.5605394840240479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45167770981788635},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.44748058915138245},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4133416414260864},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4045219421386719},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.39034149050712585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16359123587608337}],"concepts":[{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.8521329164505005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6823990345001221},{"id":"https://openalex.org/C91852762","wikidata":"https://www.wikidata.org/wiki/Q3307742","display_name":"Fitness landscape","level":3,"score":0.5605394840240479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45167770981788635},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.44748058915138245},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4133416414260864},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4045219421386719},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39034149050712585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16359123587608337},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec55065.2022.9870231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec55065.2022.9870231","pdf_url":null,"source":{"id":"https://openalex.org/S4363605353","display_name":"2022 IEEE Congress on Evolutionary Computation (CEC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W178264497","https://openalex.org/W1508767046","https://openalex.org/W1522333581","https://openalex.org/W1550160156","https://openalex.org/W1556137908","https://openalex.org/W1606456968","https://openalex.org/W1884498291","https://openalex.org/W1968921752","https://openalex.org/W1972278817","https://openalex.org/W1997807546","https://openalex.org/W2003386356","https://openalex.org/W2026484697","https://openalex.org/W2036267200","https://openalex.org/W2039906176","https://openalex.org/W2044400415","https://openalex.org/W2072441740","https://openalex.org/W2073826583","https://openalex.org/W2086209831","https://openalex.org/W2092993939","https://openalex.org/W2095199595","https://openalex.org/W2098677716","https://openalex.org/W2100791493","https://openalex.org/W2106614985","https://openalex.org/W2107425660","https://openalex.org/W2137702546","https://openalex.org/W2143095460","https://openalex.org/W2219036994","https://openalex.org/W2743199701","https://openalex.org/W2897105819","https://openalex.org/W2909673565","https://openalex.org/W2914775474","https://openalex.org/W2937748796","https://openalex.org/W4207063358","https://openalex.org/W6628852525","https://openalex.org/W6632662658","https://openalex.org/W6633277854","https://openalex.org/W6676236601"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4281837671","https://openalex.org/W2494881499"],"abstract_inverted_index":{"The":[0,148],"automated":[1,19,74,96,180],"design":[2,20,38,75,94,137,149],"of":[3,17,49,72,76,109,143,178,183],"search":[4],"techniques":[5],"is":[6,46,65,151],"a":[7,47],"recent":[8],"trend":[9],"in":[10,55],"artificial":[11],"intelligence":[12],"research.":[13],"Unfortunately,":[14],"the":[15,18,73,86,100,120,125,130,136,144,176],"majority":[16],"approaches":[21,181],"are":[22,119,172],"developed":[23],"using":[24],"trial":[25],"and":[26,106,111,114,129,162],"error":[27],"which":[28,118],"fails":[29],"to":[30,68,84,93,153,174],"justify":[31],"or":[32],"at":[33],"least":[34],"explain":[35],"why":[36],"some":[37],"decisions":[39],"succeed":[40],"while":[41],"others":[42],"fail.":[43],"This":[44,63],"approach":[45],"host":[48],"evils":[50],"as":[51],"it":[52],"has":[53,159],"resulted":[54],"poorly":[56,60],"understood":[57,61],"systems":[58],"for":[59],"problems.":[62],"study":[64],"an":[66],"attempt":[67],"improve":[69],"our":[70],"understanding":[71],"hybrid":[77],"metaheuristics":[78,113],"by":[79],"utilizing":[80],"fitness":[81],"landscape":[82],"analysis":[83],"reveal":[85],"topological":[87],"characteristics":[88],"that":[89],"can":[90],"be":[91,154],"exploited":[92],"better":[95],"approaches.":[97],"We":[98],"consider":[99],"sequential":[101],"hybridization,":[102],"including":[103],"algorithm":[104],"configuration":[105],"parameter":[107],"tuning,":[108],"single-point":[110],"multi-point":[112],"three":[115],"optimization":[116,146],"problems":[117],"earth-observing":[121],"satellite":[122],"scheduling":[123],"problem,":[124],"aircraft":[126],"landing":[127],"problem":[128],"two-dimensional":[131],"bin":[132],"packing":[133],"problem.":[134,147],"Interestingly,":[135],"space":[138,150],"exhibits":[139],"similar":[140],"trends":[141],"regardless":[142],"underlining":[145],"found":[152],"rugged,":[155],"multimodal,":[156],"moderately":[157],"searchable,":[158],"multiple":[160],"funnels,":[161],"almost":[163],"no":[164],"plateau.":[165],"Based":[166],"on":[167],"these":[168],"findings,":[169],"deeper":[170],"insights":[171],"provided":[173],"guide":[175],"development":[177],"future":[179],"instead":[182],"blindly":[184],"trying":[185],"different":[186],"options.":[187]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}