{"id":"https://openalex.org/W2065842544","doi":"https://doi.org/10.1109/tase.2013.2251881","title":"An Optimal Sample Allocation Strategy for Partition-Based Random Search","display_name":"An Optimal Sample Allocation Strategy for Partition-Based Random Search","publication_year":2013,"publication_date":"2013-04-12","ids":{"openalex":"https://openalex.org/W2065842544","doi":"https://doi.org/10.1109/tase.2013.2251881","mag":"2065842544"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2013.2251881","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2013.2251881","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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":null,"display_name":"Weiwei Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I1332737386","display_name":"General Electric (United States)","ror":"https://ror.org/013msgt25","country_code":"US","type":"company","lineage":["https://openalex.org/I1332737386"]},{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weiwei Chen","raw_affiliation_strings":["Management Sciences Lab, GE Global Research, Niskayuna, NY, USA","Manage. Sci. Lab., GE Global Res., Niskayuna, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management Sciences Lab, GE Global Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]},{"raw_affiliation_string":"Manage. Sci. Lab., GE Global Res., Niskayuna, NY, USA","institution_ids":["https://openalex.org/I1332737386"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076608196","display_name":"Siyang Gao","orcid":"https://orcid.org/0000-0002-3574-6393"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siyang Gao","raw_affiliation_strings":["Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","Dept. of Ind. & Syst. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Dept. of Ind. & Syst. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017945484","display_name":"Chun\u2010Hung Chen","orcid":"https://orcid.org/0000-0001-7824-1814"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chun-Hung Chen","raw_affiliation_strings":["Department of Systems Engineering & Operations Research, George Mason University, Fairfax, VA, USA","Dept. of Syst. Eng. & Oper. Res., George Mason Univ., Fairfax, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Systems Engineering & Operations Research, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"Dept. of Syst. Eng. & Oper. Res., George Mason Univ., Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101529205","display_name":"Leyuan Shi","orcid":"https://orcid.org/0000-0002-1397-2891"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leyuan Shi","raw_affiliation_strings":["Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","Dept. of Ind. & Syst. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Dept. of Ind. & Syst. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.3341,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.98695333,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"1","first_page":"177","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9987999796867371,"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":0.9987999796867371,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9984999895095825,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9980000257492065,"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/notation","display_name":"Notation","score":0.6547974944114685},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6236506700515747},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5066176652908325},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4930135905742645},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46640482544898987},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4613603949546814},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4341178238391876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41414201259613037},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1803065836429596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16347554326057434},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.08763235807418823}],"concepts":[{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.6547974944114685},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6236506700515747},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5066176652908325},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4930135905742645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46640482544898987},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4613603949546814},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4341178238391876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41414201259613037},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1803065836429596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16347554326057434},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.08763235807418823},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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":2,"locations":[{"id":"doi:10.1109/tase.2013.2251881","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2013.2251881","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:alma.01RUT_INST:11685491170004646","is_oa":false,"landing_page_url":"https://scholarship.libraries.rutgers.edu/esploro/outputs/journalArticle/An-Optimal-Sample-Allocation-Strategy-for/991031758999904646","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W187849000","https://openalex.org/W1499399028","https://openalex.org/W1500657154","https://openalex.org/W1536615069","https://openalex.org/W1980685536","https://openalex.org/W1986790369","https://openalex.org/W1992232665","https://openalex.org/W2015483401","https://openalex.org/W2024028161","https://openalex.org/W2025292266","https://openalex.org/W2045942883","https://openalex.org/W2047193217","https://openalex.org/W2068395502","https://openalex.org/W2069963980","https://openalex.org/W2074589987","https://openalex.org/W2115177464","https://openalex.org/W2118051273","https://openalex.org/W2119717916","https://openalex.org/W2120011574","https://openalex.org/W2132732677","https://openalex.org/W2135470049","https://openalex.org/W2137601290","https://openalex.org/W2161148706","https://openalex.org/W2166827312","https://openalex.org/W2798566347","https://openalex.org/W4234553912","https://openalex.org/W4237029372","https://openalex.org/W4237290801","https://openalex.org/W4251867147","https://openalex.org/W4301014524","https://openalex.org/W4301620610"],"related_works":["https://openalex.org/W2963177394","https://openalex.org/W2024638892","https://openalex.org/W763418848","https://openalex.org/W1595229445","https://openalex.org/W1965815883","https://openalex.org/W149041114","https://openalex.org/W4313359513","https://openalex.org/W322408318","https://openalex.org/W4298135613","https://openalex.org/W1583261078"],"abstract_inverted_index":{"Partition-based":[0],"random":[1],"search":[2],"(PRS)":[3],"provides":[4],"a":[5,17,87,98],"class":[6],"of":[7,16,53,69,77,81,119,155,165],"effective":[8,134],"algorithms":[9,140],"for":[10,43,136],"global":[11],"optimization.":[12],"In":[13,46],"each":[14,57,158],"iteration":[15,159],"PRS":[18,139,166],"algorithm,":[19],"the":[20,40,51,61,79,84,92,116,137,144,163],"solution":[21,114],"space":[22],"is":[23,35,108,123,132,153],"partitioned":[24],"into":[25],"subsets":[26],"which":[27],"are":[28,63,73],"randomly":[29],"sampled":[30],"and":[31,90,110,160],"evaluated.":[32],"One":[33],"subset":[34,42,58],"then":[36],"determined":[37],"to":[38,56,96,115],"be":[39],"promising":[41,85],"further":[44],"partitioning.":[45],"this":[47],"paper,":[48],"we":[49],"propose":[50],"problem":[52],"allocating":[54],"samples":[55,62],"so":[59],"that":[60,151],"utilized":[64],"most":[65],"efficiently.":[66],"Two":[67],"types":[68,118],"sample":[70,88,94,120,128],"allocation":[71,121,129],"problems":[72,122],"discussed,":[74],"with":[75],"objectives":[76],"maximizing":[78],"probability":[80],"correctly":[82],"selecting":[83],"subset$(P\\{CSPS\\})$given":[86],"budget":[89],"minimizing":[91],"required":[93],"size":[95],"achieve":[97],"satisfied":[99],"level":[100],"of$P\\{CSPS\\}$,":[101],"respectively.":[102],"An":[103],"extreme":[104],"value-based":[105],"prospectiveness":[106],"criterion":[107],"introduced":[109],"an":[111,133],"asymptotically":[112],"optimal":[113,127],"two":[117],"developed.":[124],"The":[125],"resulting":[126],"strategy":[130],"(OSAS)":[131],"procedure":[135],"existing":[138],"by":[141],"intelligently":[142],"utilizing":[143],"limited":[145],"computing":[146],"resources.":[147],"Numerical":[148],"tests":[149],"confirm":[150],"OSAS":[152],"capable":[154],"increasing":[156],"the$P\\{CSPS\\}$in":[157],"subsequently":[161],"improving":[162],"performance":[164],"algorithms.":[167]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":6}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}