{"id":"https://openalex.org/W3034383522","doi":"https://doi.org/10.1109/wsc.2018.8632248","title":"SEQUENTIAL FIRST-ORDER RESPONSE SURFACE METHODOLOGY AUGMENTED WITH DIRECT GRADIENTS","display_name":"SEQUENTIAL FIRST-ORDER RESPONSE SURFACE METHODOLOGY AUGMENTED WITH DIRECT GRADIENTS","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W3034383522","doi":"https://doi.org/10.1109/wsc.2018.8632248","mag":"3034383522"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2018.8632248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2018.8632248","pdf_url":null,"source":{"id":"https://openalex.org/S4363607834","display_name":"2018 Winter Simulation Conference (WSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Winter Simulation Conference (WSC)","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/A5018127028","display_name":"LI Yun-chuan","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunchuan Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, the Institute for Systems Research University of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, the Institute for Systems Research University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000889975","display_name":"Michael C. Fu","orcid":"https://orcid.org/0000-0003-2105-4932"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Fu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, the Institute for Systems Research University of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, the Institute for Systems Research University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2143","last_page":"2154"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9869999885559082,"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"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9869999885559082,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9768000245094299,"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/response-surface-methodology","display_name":"Response surface methodology","score":0.8106034994125366},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6864373683929443},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6052114963531494},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.6002242565155029},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.5877344608306885},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.48602110147476196},{"id":"https://openalex.org/keywords/gradient-method","display_name":"Gradient method","score":0.4703308045864105},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38833123445510864},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28288304805755615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16895467042922974}],"concepts":[{"id":"https://openalex.org/C150077022","wikidata":"https://www.wikidata.org/wiki/Q3136137","display_name":"Response surface methodology","level":2,"score":0.8106034994125366},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6864373683929443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6052114963531494},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.6002242565155029},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.5877344608306885},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48602110147476196},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.4703308045864105},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38833123445510864},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28288304805755615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16895467042922974},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc.2018.8632248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2018.8632248","pdf_url":null,"source":{"id":"https://openalex.org/S4363607834","display_name":"2018 Winter Simulation Conference (WSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2073503281","https://openalex.org/W2384332569","https://openalex.org/W3006216983","https://openalex.org/W2907978266","https://openalex.org/W4288908364","https://openalex.org/W4323538665","https://openalex.org/W1983047026","https://openalex.org/W2739498073","https://openalex.org/W2790579288","https://openalex.org/W2579550961"],"abstract_inverted_index":{"We":[0,46,53],"introduce":[1],"Direct":[2],"Gradient":[3],"Augmented":[4],"Response":[5,21],"Surface":[6,22],"Methodology":[7,23],"(DiGARSM),":[8],"a":[9,16],"new":[10],"sequential":[11],"first-order":[12],"method":[13],"for":[14],"optimizing":[15],"stochastic":[17],"function":[18,32],"based":[19],"on":[20],"(RSM).":[24],"In":[25],"this":[26],"approach,":[27,71],"gradients":[28],"of":[29,49,84],"the":[30,36,50,69,82,85],"objective":[31],"with":[33,68],"respect":[34],"to":[35,43,80],"desired":[37],"parameters":[38],"are":[39],"utilized":[40],"in":[41],"addition":[42],"response":[44,59],"measurements.":[45],"establish":[47],"convergence":[48],"proposed":[51,70,86],"method.":[52,87],"compare":[54],"methods":[55],"that":[56,63],"use":[57,64],"only":[58,65],"information":[60,67],"and":[61],"those":[62],"gradient":[66],"which":[72],"uses":[73],"both.":[74],"Moreover,":[75],"we":[76],"conduct":[77],"numerical":[78],"simulations":[79],"illustrate":[81],"effectiveness":[83]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}