{"id":"https://openalex.org/W4246222178","doi":"https://doi.org/10.1145/2464576.2480804","title":"Fitness landscapes and graphs","display_name":"Fitness landscapes and graphs","publication_year":2013,"publication_date":"2013-07-06","ids":{"openalex":"https://openalex.org/W4246222178","doi":"https://doi.org/10.1145/2464576.2480804"},"language":"en","primary_location":{"id":"doi:10.1145/2464576.2480804","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2464576.2480804","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th annual conference companion on Genetic and evolutionary computation","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/A5078220546","display_name":"Seb\u00e1stien V\u00e9rel","orcid":"https://orcid.org/0000-0003-1661-4093"},"institutions":[{"id":"https://openalex.org/I201841394","display_name":"Universit\u00e9 C\u00f4te d'Azur","ror":"https://ror.org/019tgvf94","country_code":"FR","type":"education","lineage":["https://openalex.org/I201841394"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Sebastien Verel","raw_affiliation_strings":["universite Nice Sophia Antipolis, Sophia Antipolis, France"],"affiliations":[{"raw_affiliation_string":"universite Nice Sophia Antipolis, Sophia Antipolis, France","institution_ids":["https://openalex.org/I201841394"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5078220546"],"corresponding_institution_ids":["https://openalex.org/I201841394"],"apc_list":null,"apc_paid":null,"fwci":0.93142169,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.88925173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"256","issue":null,"first_page":"591","last_page":"616"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11252","display_name":"Evolutionary Game Theory and Cooperation","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11252","display_name":"Evolutionary Game Theory and Cooperation","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12391","display_name":"Artificial Immune Systems Applications","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9739000201225281,"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/fitness-landscape","display_name":"Fitness landscape","score":0.8996440172195435},{"id":"https://openalex.org/keywords/fitness-approximation","display_name":"Fitness approximation","score":0.6159414052963257},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.5928703546524048},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5628059506416321},{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.5539844036102295},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.46867236495018005},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4437880516052246},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41199636459350586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3426574468612671},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30346184968948364},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1847069263458252},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.13214266300201416},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.12633123993873596}],"concepts":[{"id":"https://openalex.org/C91852762","wikidata":"https://www.wikidata.org/wiki/Q3307742","display_name":"Fitness landscape","level":3,"score":0.8996440172195435},{"id":"https://openalex.org/C148392497","wikidata":"https://www.wikidata.org/wiki/Q16250539","display_name":"Fitness approximation","level":4,"score":0.6159414052963257},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.5928703546524048},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5628059506416321},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.5539844036102295},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.46867236495018005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4437880516052246},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41199636459350586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3426574468612671},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30346184968948364},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1847069263458252},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.13214266300201416},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.12633123993873596},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2464576.2480804","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2464576.2480804","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th annual conference companion on Genetic and evolutionary computation","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":36,"referenced_works":["https://openalex.org/W70594130","https://openalex.org/W1411006099","https://openalex.org/W1522333581","https://openalex.org/W1529900568","https://openalex.org/W1535144817","https://openalex.org/W1539029852","https://openalex.org/W1568232464","https://openalex.org/W1771661567","https://openalex.org/W1862390599","https://openalex.org/W1887330423","https://openalex.org/W1973488611","https://openalex.org/W1976215910","https://openalex.org/W1977556029","https://openalex.org/W1977940795","https://openalex.org/W2015796905","https://openalex.org/W2016851559","https://openalex.org/W2024956277","https://openalex.org/W2026401578","https://openalex.org/W2044400415","https://openalex.org/W2049092030","https://openalex.org/W2061494390","https://openalex.org/W2073853984","https://openalex.org/W2075121996","https://openalex.org/W2078236617","https://openalex.org/W2137246147","https://openalex.org/W2148278639","https://openalex.org/W2161032864","https://openalex.org/W2504494713","https://openalex.org/W2548606336","https://openalex.org/W2561675875","https://openalex.org/W2912857739","https://openalex.org/W3012079654","https://openalex.org/W4241994679","https://openalex.org/W4243468655","https://openalex.org/W4388252848","https://openalex.org/W6910606203"],"related_works":["https://openalex.org/W2036107212","https://openalex.org/W2159937791","https://openalex.org/W2164084664","https://openalex.org/W2138958036","https://openalex.org/W192154461","https://openalex.org/W1591022951","https://openalex.org/W1634842376","https://openalex.org/W1974337071","https://openalex.org/W4250294025","https://openalex.org/W3009038870"],"abstract_inverted_index":{"One":[0],"of":[1,10,21,90,100,153,162,170,182,200,203,247,255,310],"the":[2,8,46,73,122,154,163,187,201,204,245,264,270,288,302],"most":[3,29],"commonly-used":[4],"metaphors":[5],"to":[6,34,97,103,186,213,230,262],"describe":[7],"process":[9,75],"heuristic":[11],"search":[12,43,47,74,188,323],"methods":[13],"in":[14,31,44,174,217,236,267,294],"solving":[15],"combinatorial":[16,237],"optimization":[17],"problems":[18],"is":[19,159],"that":[20,83],"a":[22,53,61,67,81,135,160,179,307],"fitness":[23,92,155,166,171,205,215,265,276,281,318],"landscape.":[24,167],"The":[25,147,168,220],"landscape":[26,68,82,206,266,277],"metaphor":[27],"appears":[28],"commonly":[30],"work":[32],"related":[33],"evolutionary":[35,218],"algorithms,":[36],"however,":[37],"it":[38],"can":[39,49,84,114,128,141],"be":[40,50,77,115,129,240,260,298],"used":[41],"for":[42],"general;":[45],"space":[48],"regarded":[51],"as":[52,117,242,244,321],"spatial":[54],"structure":[55],"where":[56],"each":[57,132,157],"point":[58],"(solution)":[59],"has":[60],"height":[62],"(objective":[63],"function":[64],"value)":[65],"forming":[66],"surface.":[69],"In":[70],"this":[71,176],"scenario,":[72],"would":[76],"an":[78,143,151,198],"adaptive-walk":[79],"over":[80],"range":[85],"from":[86],"having":[87],"many":[88],"peaks":[89],"high":[91],"flanked":[93],"by":[94,134],"cliffs":[95],"falling":[96],"profound":[98],"valleys":[99],"low":[101,107],"fitness,":[102],"being":[104],"smooth,":[105],"with":[106,150,184,306],"hills":[108],"and":[109,208,225,275,287,313],"gentle":[110],"valleys.":[111],"Combinatorial":[112],"landscapes":[113,172,216,319],"seen":[116],"graphs":[118],"whose":[119],"vertices":[120],"are":[121],"possible":[123],"configurations.":[124],"If":[125],"two":[126,221,231],"configurations":[127],"transformed":[130],"into":[131],"other":[133],"suitable":[136],"operator":[137],"move,":[138],"then":[139],"we":[140],"trace":[142],"edge":[144],"between":[145,272],"them.":[146,251],"resulting":[148],"graph,":[149],"indication":[152],"at":[156],"vertex,":[158],"representation":[161],"given":[164],"problem":[165,191,273],"study":[169],"consists":[173],"analyzing":[175],"graph":[177,233],"or":[178,190],"relevant":[180],"partition":[181],"it,":[183],"respect":[185],"dynamics":[189,246],"difficulty.":[192],"This":[193],"advanced":[194],"tutorial":[195,303],"will":[196,209,239,259,297,304],"give":[197],"overview":[199],"origins":[202],"metaphor,":[207],"cover":[210],"alternative":[211],"ways":[212],"define":[214],"computation.":[219],"main":[222],"geometries:":[223],"multimodal":[224],"neutral":[226,284],"landscapes,":[227],"which":[228],"correspond":[229],"different":[232],"partitions":[234],"found":[235],"optimization,":[238],"considered,":[241],"well":[243],"metaheuristics":[248],"searching":[249],"on":[250,317],"A":[252],"short":[253],"demonstration":[254],"using":[256],"paradiseo":[257],"software":[258],"made":[261],"analyze":[263],"practice.":[268],"Furthermore,":[269],"relationship":[271],"hardness":[274],"metrics":[278],"(i.e.":[279],"autocorrelation,":[280],"distance":[282],"correlation,":[283],"degree,":[285],"etc),":[286],"local":[289],"optima":[290],"network":[291],"properties,":[292],"studied":[293],"recent":[295,314],"work,":[296],"deeply":[299],"analyzed.":[300],"Finally,":[301],"conclude":[305],"brief":[308],"survey":[309],"open":[311],"questions":[312],"research":[315],"directions":[316],"such":[320],"multiobjective":[322],"space.":[324]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}