{"id":"https://openalex.org/W2975600959","doi":"https://doi.org/10.1080/00401706.2019.1665589","title":"Sequential Model-Based Optimization for Continuous Inputs with Finite Decision Space","display_name":"Sequential Model-Based Optimization for Continuous Inputs with Finite Decision Space","publication_year":2019,"publication_date":"2019-09-24","ids":{"openalex":"https://openalex.org/W2975600959","doi":"https://doi.org/10.1080/00401706.2019.1665589","mag":"2975600959"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2019.1665589","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2019.1665589","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-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/A5100407296","display_name":"Qiong Zhang","orcid":"https://orcid.org/0000-0003-1995-2127"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiong Zhang","raw_affiliation_strings":["School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC;"],"affiliations":[{"raw_affiliation_string":"School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC;","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051424291","display_name":"Youngdeok Hwang","orcid":"https://orcid.org/0000-0001-7563-5156"},"institutions":[{"id":"https://openalex.org/I141810926","display_name":"Baruch College","ror":"https://ror.org/023qavy03","country_code":"US","type":"education","lineage":["https://openalex.org/I141810926"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Youngdeok Hwang","raw_affiliation_strings":["Paul H. Chook Department of Information Systems and Statistics, Baruch College, City University of New York, New York, NY"],"affiliations":[{"raw_affiliation_string":"Paul H. Chook Department of Information Systems and Statistics, Baruch College, City University of New York, New York, NY","institution_ids":["https://openalex.org/I141810926"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051424291"],"corresponding_institution_ids":["https://openalex.org/I141810926"],"apc_list":null,"apc_paid":null,"fwci":0.388,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64483356,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"62","issue":"4","first_page":"486","last_page":"498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9998999834060669,"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":0.9998999834060669,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9965000152587891,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9941999912261963,"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/mathematical-optimization","display_name":"Mathematical optimization","score":0.6990403532981873},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.6655449271202087},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5685529112815857},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5597871541976929},{"id":"https://openalex.org/keywords/stochastic-optimization","display_name":"Stochastic optimization","score":0.5298654437065125},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5137768387794495},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5133327841758728},{"id":"https://openalex.org/keywords/continuous-optimization","display_name":"Continuous optimization","score":0.4984095096588135},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4951271116733551},{"id":"https://openalex.org/keywords/vector-optimization","display_name":"Vector optimization","score":0.46207359433174133},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.45842304825782776},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.413017213344574},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39289379119873047},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35708463191986084},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17415529489517212},{"id":"https://openalex.org/keywords/multi-swarm-optimization","display_name":"Multi-swarm optimization","score":0.12728285789489746}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6990403532981873},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6655449271202087},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5685529112815857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5597871541976929},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.5298654437065125},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5137768387794495},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5133327841758728},{"id":"https://openalex.org/C92995354","wikidata":"https://www.wikidata.org/wiki/Q5165499","display_name":"Continuous optimization","level":4,"score":0.4984095096588135},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4951271116733551},{"id":"https://openalex.org/C164088818","wikidata":"https://www.wikidata.org/wiki/Q7917833","display_name":"Vector optimization","level":4,"score":0.46207359433174133},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.45842304825782776},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.413017213344574},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39289379119873047},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35708463191986084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17415529489517212},{"id":"https://openalex.org/C122357587","wikidata":"https://www.wikidata.org/wiki/Q6934508","display_name":"Multi-swarm optimization","level":3,"score":0.12728285789489746},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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":1,"locations":[{"id":"doi:10.1080/00401706.2019.1665589","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2019.1665589","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1491420040","https://openalex.org/W1510052597","https://openalex.org/W1524392826","https://openalex.org/W1974987571","https://openalex.org/W1991413021","https://openalex.org/W2004808074","https://openalex.org/W2020732830","https://openalex.org/W2023668266","https://openalex.org/W2026261408","https://openalex.org/W2044571476","https://openalex.org/W2061820396","https://openalex.org/W2063180182","https://openalex.org/W2066596787","https://openalex.org/W2072302356","https://openalex.org/W2077007994","https://openalex.org/W2108152153","https://openalex.org/W2141086482","https://openalex.org/W2149721706","https://openalex.org/W2155927283","https://openalex.org/W2192203593","https://openalex.org/W2331234188","https://openalex.org/W2413296822","https://openalex.org/W2553755808","https://openalex.org/W2964172739","https://openalex.org/W4297776957"],"related_works":["https://openalex.org/W2931365531","https://openalex.org/W3014573403","https://openalex.org/W4381941132","https://openalex.org/W2169974588","https://openalex.org/W2084593435","https://openalex.org/W2114881872","https://openalex.org/W2198736978","https://openalex.org/W3084133043","https://openalex.org/W2139145565","https://openalex.org/W2905297725"],"abstract_inverted_index":{"Optimization":[0],"using":[1],"stochastic":[2,24],"computer":[3,25],"experiments":[4],"is":[5,27,37,62,80],"commonplace":[6],"in":[7,18,33],"engineering":[8],"and":[9,72],"industry.":[10],"This":[11,85],"article":[12],"addresses":[13],"the":[14,20,30,34,65,73,83,90,96,99,105],"problem":[15,36],"of":[16,23,89,107],"optimization,":[17],"which":[19],"input":[21],"space":[22,32,61,93],"model":[26],"continuous,":[28],"whereas":[29],"decision":[31,60,101],"real":[35],"restricted":[38,59],"to":[39,49,67,94],"be":[40],"finite.":[41],"We":[42,103],"propose":[43],"a":[44],"sequential":[45,114],"model-based":[46,115],"optimization":[47,116],"method":[48],"tackle":[50],"this":[51,58],"problem.":[52],"The":[53],"knowledge":[54],"gradient":[55],"based":[56],"on":[57],"used":[63,81],"as":[64,82],"criterion":[66],"choose":[68],"new":[69],"design":[70],"points,":[71],"fixed":[74],"rank":[75],"kriging":[76],"or":[77],"Gaussian":[78],"process":[79],"surrogate.":[84],"combination":[86],"takes":[87],"advantage":[88],"continuous":[91],"search":[92],"decrease":[95],"uncertainty":[97],"over":[98],"finite":[100],"space.":[102],"demonstrate":[104],"benefit":[106],"our":[108],"proposed":[109],"methodology":[110],"compared":[111],"with":[112],"existing":[113],"methods.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}