{"id":"https://openalex.org/W2963901087","doi":"https://doi.org/10.1080/01605682.2019.1599779","title":"Data-driven satisficing measure and ranking","display_name":"Data-driven satisficing measure and ranking","publication_year":2019,"publication_date":"2019-04-25","ids":{"openalex":"https://openalex.org/W2963901087","doi":"https://doi.org/10.1080/01605682.2019.1599779","mag":"2963901087"},"language":"en","primary_location":{"id":"doi:10.1080/01605682.2019.1599779","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01605682.2019.1599779","pdf_url":null,"source":{"id":"https://openalex.org/S169988927","display_name":"Journal of the Operational Research Society","issn_l":"0160-5682","issn":["0160-5682","1476-9360"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319703","host_organization_name":"Palgrave Macmillan","host_organization_lineage":["https://openalex.org/P4310319703","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Palgrave Macmillan","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Operational Research Society","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/A5070019149","display_name":"Wenjie Huang","orcid":"https://orcid.org/0000-0002-1358-213X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Wenjie Huang","raw_affiliation_strings":["Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070019149"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.2063,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58805123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"71","issue":"3","first_page":"456","last_page":"474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11413","display_name":"Risk and Portfolio Optimization","score":0.9998999834060669,"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/T11413","display_name":"Risk and Portfolio Optimization","score":0.9998999834060669,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9842000007629395,"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/satisficing","display_name":"Satisficing","score":0.6964293122291565},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6899959444999695},{"id":"https://openalex.org/keywords/risk-measure","display_name":"Risk measure","score":0.6102125644683838},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6037721037864685},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5934438705444336},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5588746666908264},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5343474745750427},{"id":"https://openalex.org/keywords/expected-shortfall","display_name":"Expected shortfall","score":0.4759361743927002},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4120485782623291},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33177316188812256},{"id":"https://openalex.org/keywords/risk-management","display_name":"Risk management","score":0.3015674948692322},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2165473997592926},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17300954461097717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1620197594165802},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.08905240893363953}],"concepts":[{"id":"https://openalex.org/C94822996","wikidata":"https://www.wikidata.org/wiki/Q1777902","display_name":"Satisficing","level":2,"score":0.6964293122291565},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6899959444999695},{"id":"https://openalex.org/C2781472820","wikidata":"https://www.wikidata.org/wiki/Q2154759","display_name":"Risk measure","level":3,"score":0.6102125644683838},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6037721037864685},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5934438705444336},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5588746666908264},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5343474745750427},{"id":"https://openalex.org/C5496284","wikidata":"https://www.wikidata.org/wiki/Q5420856","display_name":"Expected shortfall","level":3,"score":0.4759361743927002},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4120485782623291},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33177316188812256},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.3015674948692322},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2165473997592926},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17300954461097717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1620197594165802},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.08905240893363953},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/01605682.2019.1599779","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01605682.2019.1599779","pdf_url":null,"source":{"id":"https://openalex.org/S169988927","display_name":"Journal of the Operational Research Society","issn_l":"0160-5682","issn":["0160-5682","1476-9360"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319703","host_organization_name":"Palgrave Macmillan","host_organization_lineage":["https://openalex.org/P4310319703","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Palgrave Macmillan","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Operational Research Society","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:taf:tjorxx:v:71:y:2020:i:3:p:456-474","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/01605682.2019.1599779","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W315644267","https://openalex.org/W1499021337","https://openalex.org/W1647779468","https://openalex.org/W1832379062","https://openalex.org/W1968355947","https://openalex.org/W1972105687","https://openalex.org/W1976406849","https://openalex.org/W1981048380","https://openalex.org/W1994616650","https://openalex.org/W2007181101","https://openalex.org/W2009797711","https://openalex.org/W2013784666","https://openalex.org/W2019291268","https://openalex.org/W2032216509","https://openalex.org/W2034320649","https://openalex.org/W2035574843","https://openalex.org/W2045115089","https://openalex.org/W2050701458","https://openalex.org/W2068506505","https://openalex.org/W2068870786","https://openalex.org/W2069826626","https://openalex.org/W2077723394","https://openalex.org/W2078690215","https://openalex.org/W2081081544","https://openalex.org/W2093135704","https://openalex.org/W2094536313","https://openalex.org/W2113991325","https://openalex.org/W2114433987","https://openalex.org/W2115001337","https://openalex.org/W2116731530","https://openalex.org/W2116956106","https://openalex.org/W2119239894","https://openalex.org/W2121468937","https://openalex.org/W2121946341","https://openalex.org/W2128422927","https://openalex.org/W2134125848","https://openalex.org/W2134802631","https://openalex.org/W2137385155","https://openalex.org/W2138862581","https://openalex.org/W2146502635","https://openalex.org/W2148091045","https://openalex.org/W2148962857","https://openalex.org/W2155581291","https://openalex.org/W2158928097","https://openalex.org/W2167038379","https://openalex.org/W2170419304","https://openalex.org/W2219315558","https://openalex.org/W2221340659","https://openalex.org/W2288802042","https://openalex.org/W2296319761","https://openalex.org/W2535146975","https://openalex.org/W2565566557","https://openalex.org/W2594297742","https://openalex.org/W2762195323","https://openalex.org/W2790973836","https://openalex.org/W3123061825","https://openalex.org/W3123325486","https://openalex.org/W3123429966","https://openalex.org/W3125145310","https://openalex.org/W4212901515","https://openalex.org/W4250589301","https://openalex.org/W4292022450","https://openalex.org/W4296400122"],"related_works":["https://openalex.org/W2408851247","https://openalex.org/W3121825436","https://openalex.org/W4301377905","https://openalex.org/W2950198523","https://openalex.org/W799577184","https://openalex.org/W2373247897","https://openalex.org/W291419825","https://openalex.org/W2112426182","https://openalex.org/W3083534660","https://openalex.org/W1978849664"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,32,41,45],"computational":[3],"framework":[4],"for":[5,11,35,44,96],"real-time":[6],"risk":[7,36,48,57,98,117],"assessment":[8],"and":[9,59,74,79,101,109],"prioritising":[10],"random":[12],"outcomes":[13],"without":[14],"prior":[15],"information":[16],"on":[17,26],"probability":[18],"distributions.":[19],"The":[20],"basic":[21],"model":[22],"is":[23,40],"built":[24],"based":[25],"satisficing":[27],"measure":[28],"(SM)":[29],"which":[30],"yields":[31],"single":[33],"index":[34],"comparison.":[37],"Since":[38],"SM":[39],"dual":[42],"representation":[43],"family":[46],"of":[47,81],"measures,":[49],"we":[50,68,89,112],"consider":[51],"problems":[52],"constrained":[53,99],"by":[54,61],"general":[55,97],"convex":[56],"measures":[58],"specifically":[60],"conditional":[62],"value-at-risk.":[63],"Starting":[64],"from":[65],"offline":[66,108],"optimisation,":[67],"apply":[69],"sample":[70,121],"average":[71],"approximation":[72,93],"technique":[73],"argue":[75],"the":[76,114],"convergence":[77],"rate":[78],"validation":[80],"optimal":[82],"solutions.":[83],"In":[84],"online":[85,110],"stochastic":[86,92],"optimisation":[87],"case,":[88],"develop":[90],"primal-dual":[91],"algorithms":[94],"respectively":[95],"problems,":[100],"derive":[102],"their":[103],"regret":[104],"bounds.":[105],"For":[106],"both":[107],"cases,":[111],"illustrate":[113],"relationship":[115],"between":[116],"ranking":[118],"accuracy":[119],"with":[120],"size":[122],"(or":[123],"iterations).":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}