{"id":"https://openalex.org/W1975553566","doi":"https://doi.org/10.1109/cec.2007.4424773","title":"An approach for multi-objective robust optimization assisted by response surface approximation and visual data-mining","display_name":"An approach for multi-objective robust optimization assisted by response surface approximation and visual data-mining","publication_year":2007,"publication_date":"2007-09-01","ids":{"openalex":"https://openalex.org/W1975553566","doi":"https://doi.org/10.1109/cec.2007.4424773","mag":"1975553566"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2007.4424773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2007.4424773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Congress on Evolutionary Computation","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/A5065411208","display_name":"Koji Shimoyama","orcid":"https://orcid.org/0000-0001-8896-7707"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Shimoyama","raw_affiliation_strings":["Intitute of Fluid Science, University of Tohoku, Sendai, Japan","Tohoku University, Sendai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intitute of Fluid Science, University of Tohoku, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]},{"raw_affiliation_string":"Tohoku University, Sendai","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061510492","display_name":"Jin Ne Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jin Ne Lim","raw_affiliation_strings":["Intitute of Fluid Science, University of Tohoku, Sendai, Japan","Tohoku University, Sendai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intitute of Fluid Science, University of Tohoku, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]},{"raw_affiliation_string":"Tohoku University, Sendai","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102000209","display_name":"Shinkyu Jeong","orcid":"https://orcid.org/0000-0002-8929-4820"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinkyu Jeong","raw_affiliation_strings":["Intitute of Fluid Science, University of Tohoku, Sendai, Japan","Tohoku University, Sendai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intitute of Fluid Science, University of Tohoku, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]},{"raw_affiliation_string":"Tohoku University, Sendai","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009004761","display_name":"Shigeru Obayashi","orcid":"https://orcid.org/0000-0003-3876-1908"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigeru Obayashi","raw_affiliation_strings":["Intitute of Fluid Science, University of Tohoku, Sendai, Japan","Tohoku University, Sendai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intitute of Fluid Science, University of Tohoku, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]},{"raw_affiliation_string":"Tohoku University, Sendai","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112229721","display_name":"Masataka KOISHI","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108878","display_name":"Yokohama Rubber (Japan)","ror":"https://ror.org/01zwphm70","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210108878"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masataka Koishi","raw_affiliation_strings":["Research and Technology Develoment Department, Yokohama Rubber Company Limited, Hiratsuka, Kanagawa, Japan","Tire Research and Technology Development Dept., Yokohama Rubber Co., Ltd., 2-1 Oiwake, Hiratsuka, Kanagawa, 2548610, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research and Technology Develoment Department, Yokohama Rubber Company Limited, Hiratsuka, Kanagawa, Japan","institution_ids":["https://openalex.org/I4210108878"]},{"raw_affiliation_string":"Tire Research and Technology Development Dept., Yokohama Rubber Co., Ltd., 2-1 Oiwake, Hiratsuka, Kanagawa, 2548610, Japan","institution_ids":["https://openalex.org/I4210108878"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2413","last_page":"2420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.9884999990463257,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.9150813817977905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7223788499832153},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6312209367752075},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5936228632926941},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47250115871429443},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.46177470684051514},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.42713114619255066},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41597625613212585},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37145835161209106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3568193316459656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28656917810440063},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17322176694869995}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.9150813817977905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7223788499832153},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6312209367752075},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5936228632926941},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47250115871429443},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.46177470684051514},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.42713114619255066},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41597625613212585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37145835161209106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3568193316459656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28656917810440063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17322176694869995},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2007.4424773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2007.4424773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Congress on 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":17,"referenced_works":["https://openalex.org/W1510052597","https://openalex.org/W1514048016","https://openalex.org/W1595498733","https://openalex.org/W1607768087","https://openalex.org/W1612556207","https://openalex.org/W1679913846","https://openalex.org/W1999923502","https://openalex.org/W2018044188","https://openalex.org/W2038669746","https://openalex.org/W2110603253","https://openalex.org/W2160910185","https://openalex.org/W2261054240","https://openalex.org/W4237948290","https://openalex.org/W4243645092","https://openalex.org/W6636486754","https://openalex.org/W6636658889","https://openalex.org/W6637308636"],"related_works":["https://openalex.org/W2013728941","https://openalex.org/W4225274103","https://openalex.org/W2154046714","https://openalex.org/W2189613078","https://openalex.org/W2579659702","https://openalex.org/W2923661510","https://openalex.org/W1574055964","https://openalex.org/W1965329638","https://openalex.org/W2542318691","https://openalex.org/W3160708108"],"abstract_inverted_index":{"A":[0],"new":[1],"approach":[2,27],"for":[3,52,69],"multi-objective":[4],"robust":[5],"design":[6,16,88,95,123],"optimization":[7],"has":[8],"been":[9],"proposed":[10],"and":[11,34,46,63,92,104,111,115],"applied":[12],"to":[13],"a":[14,19,81,97,129],"real-world":[15],"problem":[17],"with":[18],"large":[20],"number":[21],"of":[22,60,77,86,94,106,113,119],"objective":[23,70],"functions.":[24],"The":[25,49],"present":[26],"is":[28],"assisted":[29],"by":[30],"response":[31,53],"surface":[32,54],"approximation":[33,55],"visual":[35],"data-mining,":[36],"which":[37],"results":[38],"in":[39,96,121,128],"two":[40],"major":[41],"gains":[42],"regarding":[43],"computational":[44,67],"time":[45,68],"data":[47],"interpretation.":[48],"Kriging":[50],"model":[51],"can":[56,125],"realize":[57],"accurate":[58],"predictions":[59],"robustness":[61,93,112],"measures,":[62],"dramatically":[64],"reduces":[65],"the":[66,75,102,117,122],"function":[71],"evaluation.":[72],"In":[73],"addition,":[74],"use":[76],"self-organizing":[78],"maps":[79],"as":[80],"datamining":[82],"technique":[83],"allows":[84],"visualization":[85],"complicated":[87],"information":[89],"between":[90,109],"optimality":[91,110],"comprehensible":[98],"two-dimensional":[99],"form.":[100],"Therefore,":[101],"extraction":[103],"interpretation":[105],"trade-off":[107],"relations":[108],"design,":[114],"also":[116],"location":[118],"sweet-spots":[120],"space,":[124],"be":[126],"performed":[127],"comprehensive":[130],"manner.":[131]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
