{"id":"https://openalex.org/W1963922147","doi":"https://doi.org/10.1145/1389095.1389191","title":"Aiming for a theoretically tractable CSA variant by means of empirical investigations","display_name":"Aiming for a theoretically tractable CSA variant by means of empirical investigations","publication_year":2008,"publication_date":"2008-07-12","ids":{"openalex":"https://openalex.org/W1963922147","doi":"https://doi.org/10.1145/1389095.1389191","mag":"1963922147"},"language":"en","primary_location":{"id":"doi:10.1145/1389095.1389191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1389095.1389191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th annual conference 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/A5033973518","display_name":"Jens J\u00e4gersk\u00fcpper","orcid":null},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jens J\u00e4gersk\u00fcpper","raw_affiliation_strings":["TU Dortmund, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"TU Dortmund, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062774048","display_name":"Mike Preu\u00df","orcid":"https://orcid.org/0000-0003-4681-1346"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mike Preuss","raw_affiliation_strings":["TU Dortmund, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"TU Dortmund, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033973518"],"corresponding_institution_ids":["https://openalex.org/I200332995"],"apc_list":null,"apc_paid":null,"fwci":1.1441,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83084586,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"503","last_page":"510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9991000294685364,"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":0.9980000257492065,"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.5992712378501892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5496948957443237},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5383734107017517},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5170348286628723},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5126294493675232},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.48876166343688965},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.4872668981552124},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.46210727095603943},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4576493799686432},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4575369358062744},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.44024717807769775},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4330727458000183},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3498639166355133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34866246581077576},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2145480215549469},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21283027529716492},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1990472674369812}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5992712378501892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5496948957443237},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5383734107017517},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5170348286628723},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5126294493675232},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.48876166343688965},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4872668981552124},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.46210727095603943},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4576493799686432},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4575369358062744},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.44024717807769775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4330727458000183},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3498639166355133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34866246581077576},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2145480215549469},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21283027529716492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1990472674369812},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1389095.1389191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1389095.1389191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th annual conference 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":13,"referenced_works":["https://openalex.org/W1485111065","https://openalex.org/W1498178627","https://openalex.org/W1520299729","https://openalex.org/W2023782941","https://openalex.org/W2046261509","https://openalex.org/W2101677491","https://openalex.org/W2121811374","https://openalex.org/W2162737890","https://openalex.org/W2165220807","https://openalex.org/W2235047952","https://openalex.org/W3029645440","https://openalex.org/W4213261160","https://openalex.org/W4293775970"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W2047881532","https://openalex.org/W4293088233","https://openalex.org/W2285795935","https://openalex.org/W4389072557","https://openalex.org/W1991765889","https://openalex.org/W1990068454","https://openalex.org/W2472172556","https://openalex.org/W4319452366","https://openalex.org/W2221502901"],"abstract_inverted_index":{"Evolution":[0,38],"Strategies":[1,39],"(ES)":[2],"for":[3,20,55],"black-box":[4],"optimization":[5],"of":[6,23,43,74,80,91],"a":[7,70,81,88],"function":[8,105],"f:Rn->R":[9],"are":[10,29,45],"investigated.":[11],"Namely,":[12],"we":[13,97],"consider":[14,98],"the":[15,21,84,103],"cumulative":[16],"step-size":[17,93],"adaptation":[18],"(CSA)":[19],"variance":[22],"multivariate":[24],"zero-mean":[25],"normal":[26],"distributions,":[27],"which":[28],"commonly":[30],"used":[31],"to":[32,68],"sample":[33],"new":[34,58],"candidate":[35],"solutions":[36],"within":[37],"(ES).":[40],"Four":[41],"simplifications":[42],"CSA":[44,82],"proposed":[46],"and":[47,50,87,107],"investigated":[48],"empirically":[49],"evaluated":[51],"statistically.":[52],"The":[53],"background":[54],"these":[56],"four":[57],"CSA-derivatives,":[59],"however,":[60],"is":[61],"NOT":[62],"performance":[63],"tuning,":[64],"but":[65],"our":[66],"aim":[67],"accomplish":[69],"probabilistic/theoretical":[71],"runtime":[72],"analysis":[73],"an":[75],"ES":[76],"using":[77],"some":[78],"kind":[79],"in":[83],"near":[85],"future,":[86],"better":[89],"understanding":[90],"this":[92],"control":[94],"mechanisms.":[95],"Therefore,":[96],"two":[99],"test":[100],"problems,":[101],"namely":[102],"Sphere":[104],"without":[106],"with":[108],"Gaussian":[109],"noise.":[110]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}