{"id":"https://openalex.org/W4232944679","doi":"https://doi.org/10.1109/wsc.2013.6721411","title":"Allocating attribute-specific information-gathering resources to improve selection decisions","display_name":"Allocating attribute-specific information-gathering resources to improve selection decisions","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W4232944679","doi":"https://doi.org/10.1109/wsc.2013.6721411"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2013.6721411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2013.6721411","pdf_url":null,"source":{"id":"https://openalex.org/S4363607809","display_name":"2013 Winter Simulations 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":"2013 Winter Simulations Conference (WSC)","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/A5049629242","display_name":"Dennis D. Leber","orcid":null},"institutions":[{"id":"https://openalex.org/I1321296531","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416","country_code":"US","type":"funder","lineage":["https://openalex.org/I1321296531","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dennis D. Leber","raw_affiliation_strings":["National Institute of Standards and Technology, Gaithersburg, MD, USA"],"affiliations":[{"raw_affiliation_string":"National Institute of Standards and Technology, Gaithersburg, MD, USA","institution_ids":["https://openalex.org/I1321296531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074307288","display_name":"Jeffrey W. Herrmann","orcid":"https://orcid.org/0000-0002-4081-1196"},"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":"Jeffrey W. Herrmann","raw_affiliation_strings":["A. James Clark School of Engineering, University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"A. James Clark School of Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049629242"],"corresponding_institution_ids":["https://openalex.org/I1321296531"],"apc_list":null,"apc_paid":null,"fwci":0.4811,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64251969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9718999862670898,"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":0.9718999862670898,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9714999794960022,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9635999798774719,"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/computer-science","display_name":"Computer science","score":0.7067139148712158},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6529140472412109},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5885568261146545},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5276735424995422},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.48710107803344727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4812628924846649},{"id":"https://openalex.org/keywords/efficient-frontier","display_name":"Efficient frontier","score":0.4519512355327606},{"id":"https://openalex.org/keywords/decision-rule","display_name":"Decision rule","score":0.4290618598461151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31615912914276123},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3015422224998474}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067139148712158},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6529140472412109},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5885568261146545},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5276735424995422},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.48710107803344727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4812628924846649},{"id":"https://openalex.org/C51485801","wikidata":"https://www.wikidata.org/wiki/Q16966861","display_name":"Efficient frontier","level":3,"score":0.4519512355327606},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.4290618598461151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31615912914276123},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3015422224998474},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/wsc.2013.6721411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2013.6721411","pdf_url":null,"source":{"id":"https://openalex.org/S4363607809","display_name":"2013 Winter Simulations 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":"2013 Winter Simulations Conference (WSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.367.9607","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.367.9607","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isr.umd.edu/~jwh2/papers/Leber-Herrmann.WSC2013.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.661.8773","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.661.8773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://informs-sim.org/wsc13papers/includes/files/009.pdf","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":7,"referenced_works":["https://openalex.org/W2014018052","https://openalex.org/W2122470810","https://openalex.org/W2244525737","https://openalex.org/W2486444208","https://openalex.org/W2993459580","https://openalex.org/W4211067740","https://openalex.org/W4254385646"],"related_works":["https://openalex.org/W2392157072","https://openalex.org/W4205762803","https://openalex.org/W2535856026","https://openalex.org/W2265065644","https://openalex.org/W4283834572","https://openalex.org/W2790591938","https://openalex.org/W2134699697","https://openalex.org/W3017188156","https://openalex.org/W2322875716","https://openalex.org/W4323322994"],"abstract_inverted_index":{"When":[0],"collecting":[1],"data":[2],"to":[3,23,105],"select":[4],"an":[5,56],"alternative":[6],"from":[7],"a":[8,36,68,75,106,136],"finite":[9],"set":[10],"of":[11,31,54,74,84,86,98,144],"alternatives":[12,66],"that":[13,25,81,109,121],"are":[14,44],"described":[15],"by":[16],"multiple":[17],"attributes,":[18],"one":[19],"must":[20],"allocate":[21],"effort":[22],"activities":[24],"provide":[26],"information":[27],"about":[28,94],"the":[29,41,52,63,87,95,99,112,116,126,142],"value":[30,127],"each":[32],"attribute.":[33],"This":[34,49],"is":[35],"particularly":[37],"relevant":[38],"problem":[39,53],"when":[40,62,91],"attribute":[42],"values":[43],"estimated":[45],"using":[46],"experimental":[47,57,113],"data.":[48],"paper":[50],"discusses":[51],"allocating":[55],"budget":[58,114],"amongst":[59],"two":[60],"attributes":[61],"non-dominated":[64],"decision":[65,88],"form":[67],"concave":[69],"efficient":[70],"frontier.":[71,100],"The":[72],"results":[73],"simulation":[76],"study":[77],"suggested":[78],"allocation":[79],"rules":[80,102],"take":[82],"advantage":[83],"knowledge":[85,93],"model":[89],"and,":[90],"available,":[92],"general":[96],"shape":[97],"These":[101],"were":[103],"compared":[104],"default":[107],"rule":[108,120,140],"equally":[110],"allocated":[111,122],"across":[115,147],"attributes.":[117],"A":[118],"proportional":[119],"samples":[123],"based":[124],"on":[125],"function":[128],"weights":[129],"performed":[130],"well":[131],"only":[132],"in":[133],"some":[134],"cases;":[135],"more":[137],"sophisticated":[138],"step":[139],"increased":[141],"frequency":[143],"correct":[145],"selection":[146],"all":[148],"weights.":[149]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}