{"id":"https://openalex.org/W2922325563","doi":"https://doi.org/10.1109/cdc40024.2019.9030247","title":"The Scenario Approach Meets Uncertain Game Theory and Variational Inequalities","display_name":"The Scenario Approach Meets Uncertain Game Theory and Variational Inequalities","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2922325563","doi":"https://doi.org/10.1109/cdc40024.2019.9030247","mag":"2922325563"},"language":"en","primary_location":{"id":"doi:10.1109/cdc40024.2019.9030247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9030247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.06762","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Dario Paccagnan","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dario Paccagnan","raw_affiliation_strings":["Mechanical Engineering Department and the Center of Control, UC Santa, Barbara, CA, USA"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department and the Center of Control, UC Santa, Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":null,"display_name":"Marco C. Campi","orcid":null},"institutions":[{"id":"https://openalex.org/I79940851","display_name":"University of Brescia","ror":"https://ror.org/02q2d2610","country_code":"IT","type":"education","lineage":["https://openalex.org/I79940851"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marco C. Campi","raw_affiliation_strings":["Dipartimento di Ingegneria dell\u2019Informazione, Universit\u00e0 di Brescia, Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell\u2019Informazione, Universit\u00e0 di Brescia, Italy","institution_ids":["https://openalex.org/I79940851"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154570441"],"apc_list":null,"apc_paid":null,"fwci":4.2601,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.92603748,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11413","display_name":"Risk and Portfolio Optimization","score":0.9955999851226807,"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/T10545","display_name":"Optimization and Variational Analysis","score":0.9908000230789185,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/variational-inequality","display_name":"Variational inequality","score":0.7365999817848206},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6319000124931335},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6018000245094299},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5626999735832214},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.541100025177002},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5182999968528748},{"id":"https://openalex.org/keywords/game-theory","display_name":"Game theory","score":0.511900007724762},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3725999891757965}],"concepts":[{"id":"https://openalex.org/C161999928","wikidata":"https://www.wikidata.org/wiki/Q4556320","display_name":"Variational inequality","level":2,"score":0.7365999817848206},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6319000124931335},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6018000245094299},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5777999758720398},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5626999735832214},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.541100025177002},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5182999968528748},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.511900007724762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47440001368522644},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.3521000146865845},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34130001068115234},{"id":"https://openalex.org/C523394659","wikidata":"https://www.wikidata.org/wiki/Q17086892","display_name":"Variational analysis","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C45555294","wikidata":"https://www.wikidata.org/wiki/Q28113351","display_name":"Inequality","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C3309286","wikidata":"https://www.wikidata.org/wiki/Q4907693","display_name":"Bilevel optimization","level":3,"score":0.2632000148296356},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cdc40024.2019.9030247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9030247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1903.06762","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.06762","pdf_url":"https://arxiv.org/pdf/1903.06762","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/83320","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/83320","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1903.06762","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.06762","pdf_url":"https://arxiv.org/pdf/1903.06762","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W183050033","https://openalex.org/W617406872","https://openalex.org/W1784291829","https://openalex.org/W1976466849","https://openalex.org/W2008896163","https://openalex.org/W2010659474","https://openalex.org/W2015893008","https://openalex.org/W2061625950","https://openalex.org/W2066111511","https://openalex.org/W2078816386","https://openalex.org/W2088077079","https://openalex.org/W2094435766","https://openalex.org/W2094446970","https://openalex.org/W2117781171","https://openalex.org/W2125913552","https://openalex.org/W2164261482","https://openalex.org/W2177752066","https://openalex.org/W2181730996","https://openalex.org/W2481731143","https://openalex.org/W2576030550","https://openalex.org/W2593263173","https://openalex.org/W2763189502","https://openalex.org/W2804656365","https://openalex.org/W2922325563"],"related_works":[],"abstract_inverted_index":{"Variational":[0],"inequalities":[1],"are":[2],"modeling":[3],"tools":[4],"used":[5],"to":[6,30,52,67,100],"capture":[7],"a":[8,25,143],"variety":[9],"of":[10,27,48,57,64,73,88,103,136],"decision-making":[11],"problems":[12,65],"arising":[13],"in":[14,113,118,125],"mathematical":[15],"optimization,":[16],"operations":[17],"research,":[18,58],"game":[19],"theory.":[20],"The":[21,45],"scenario":[22,75],"approach":[23],"is":[24,51],"set":[26],"techniques":[28],"developed":[29],"tackle":[31],"stochastic":[32],"optimization":[33],"problems,":[34],"take":[35],"decisions":[36],"based":[37],"on":[38,142],"historical":[39],"data,":[40],"and":[41,59,78,90,134],"quantify":[42],"their":[43],"risk.":[44],"overarching":[46],"goal":[47],"this":[49],"manuscript":[50],"bridge":[53],"these":[54,98],"two":[55,101],"areas":[56],"thus":[60],"broaden":[61],"the":[62,71,74,86,107,110,114,119,122,126,132],"class":[63,121],"amenable":[66],"be":[68],"studied":[69],"under":[70],"lens":[72],"approach.":[76],"First":[77],"foremost,":[79],"we":[80,96,130],"provide":[81],"out-of-samples":[82],"feasibility":[83],"guarantees":[84],"for":[85],"solution":[87],"variational":[89,92],"quasi":[91],"inequality":[93],"problems.":[94],"Second,":[95],"apply":[97],"results":[99],"classes":[102],"uncertain":[104],"games.":[105],"In":[106],"first":[108],"class,":[109],"uncertainty":[111,123],"enters":[112,124],"constraint":[115],"sets,":[116],"while":[117],"second":[120],"cost":[127],"functions.":[128],"Finally,":[129],"exemplify":[131],"quality":[133],"relevance":[135],"our":[137],"bounds":[138],"through":[139],"numerical":[140],"simulations":[141],"demand-response":[144],"model.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-03-22T00:00:00"}
