{"id":"https://openalex.org/W2986657821","doi":"https://doi.org/10.1109/cdc40024.2019.9030211","title":"QPALM: A Newton-type Proximal Augmented Lagrangian Method for Quadratic Programs","display_name":"QPALM: A Newton-type Proximal Augmented Lagrangian Method for Quadratic Programs","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2986657821","doi":"https://doi.org/10.1109/cdc40024.2019.9030211","mag":"2986657821"},"language":"en","primary_location":{"id":"doi:10.1109/cdc40024.2019.9030211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9030211","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/1911.02934","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ben Hermans","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116480","display_name":"Flanders Make (Belgium)","ror":"https://ror.org/02ndjfz59","country_code":"BE","type":"company","lineage":["https://openalex.org/I4210116480"]},{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Ben Hermans","raw_affiliation_strings":["Department of Mechanical Engineering, KU Leuven, and DMMS lab, Flanders Make, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, KU Leuven, and DMMS lab, Flanders Make, Leuven, Belgium","institution_ids":["https://openalex.org/I4210116480","https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andreas Themelis","orcid":null},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Andreas Themelis","raw_affiliation_strings":["Department of Electrical Engineering (ESAT-STADIUS), KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering (ESAT-STADIUS), KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":null,"display_name":"Panagiotis Patrinos","orcid":null},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Panagiotis Patrinos","raw_affiliation_strings":["Department of Electrical Engineering (ESAT-STADIUS), KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering (ESAT-STADIUS), KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5758,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82652091,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4325","last_page":"4330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10545","display_name":"Optimization and Variational Analysis","score":0.989799976348877,"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/solver","display_name":"Solver","score":0.6905999779701233},{"id":"https://openalex.org/keywords/augmented-lagrangian-method","display_name":"Augmented Lagrangian method","score":0.6570000052452087},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.5584999918937683},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5098999738693237},{"id":"https://openalex.org/keywords/line-search","display_name":"Line search","score":0.507099986076355},{"id":"https://openalex.org/keywords/quadratic-programming","display_name":"Quadratic programming","score":0.4731999933719635},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4602000117301941},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.4596000015735626},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4325999915599823},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4138999879360199}],"concepts":[{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6905999779701233},{"id":"https://openalex.org/C150452318","wikidata":"https://www.wikidata.org/wiki/Q4820432","display_name":"Augmented Lagrangian method","level":2,"score":0.6570000052452087},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.598800003528595},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5479000210762024},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5098999738693237},{"id":"https://openalex.org/C85522705","wikidata":"https://www.wikidata.org/wiki/Q3278015","display_name":"Line search","level":3,"score":0.507099986076355},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4643000066280365},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4602000117301941},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.43380001187324524},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C17095337","wikidata":"https://www.wikidata.org/wiki/Q2375229","display_name":"Piecewise linear function","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C198927703","wikidata":"https://www.wikidata.org/wiki/Q4373881","display_name":"Sequential quadratic programming","level":3,"score":0.350600004196167},{"id":"https://openalex.org/C85189116","wikidata":"https://www.wikidata.org/wiki/Q374195","display_name":"Newton's method","level":3,"score":0.3499999940395355},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C520416788","wikidata":"https://www.wikidata.org/wiki/Q5419229","display_name":"Exact solutions in general relativity","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3228999972343445},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.31380000710487366},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2775000035762787},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C115527620","wikidata":"https://www.wikidata.org/wiki/Q769909","display_name":"Nonlinear programming","level":3,"score":0.2632000148296356},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cdc40024.2019.9030211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9030211","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:1911.02934","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.02934","pdf_url":"https://arxiv.org/pdf/1911.02934","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:lirias2repo.kuleuven.be:123456789/639725","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/bitstream/123456789/639725/3/CDC2019.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019 IEEE Conference on Decision and Control (CDC), Nice, France, 11-13 December 2019","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.02934","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.02934","pdf_url":"https://arxiv.org/pdf/1911.02934","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":15,"referenced_works":["https://openalex.org/W646582900","https://openalex.org/W1983864916","https://openalex.org/W1985496293","https://openalex.org/W2013439434","https://openalex.org/W2021721734","https://openalex.org/W2034852479","https://openalex.org/W2089024363","https://openalex.org/W2112883920","https://openalex.org/W2135779729","https://openalex.org/W2962951092","https://openalex.org/W2963190023","https://openalex.org/W4244393449","https://openalex.org/W6608335870","https://openalex.org/W6674958657","https://openalex.org/W6755659507"],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,40,59,126],"proximal":[3],"augmented":[4],"Lagrangian":[5],"based":[6],"solver":[7],"for":[8,125],"general":[9],"quadratic":[10],"programs":[11],"(QPs),":[12],"relying":[13],"on":[14,73],"semismooth":[15],"Newton":[16],"iterations":[17],"with":[18],"exact":[19,28],"line":[20,29],"search":[21,30],"to":[22,35,69,97,134],"solve":[23],"the":[24,37,56,67,74,113],"inner":[25],"subproblems.":[26],"The":[27],"reduces":[31],"in":[32,85],"this":[33],"case":[34],"finding":[36],"zero":[38],"of":[39,58,112,129],"one-dimensional":[41],"monotone,":[42],"piecewise":[43],"affine":[44],"function":[45],"and":[46,90,100,118,132],"can":[47,81,93,103],"be":[48,70,82,94,104],"carried":[49],"out":[50],"very":[51],"efficiently.":[52],"Our":[53],"algorithm":[54,115],"requires":[55],"solution":[57],"linear":[60],"system":[61],"at":[62],"every":[63],"iteration,":[64],"but":[65],"as":[66],"matrix":[68],"factorized":[71],"depends":[72],"active":[75],"constraints,":[76],"efficient":[77],"sparse":[78],"factorization":[79],"updates":[80],"employed":[83],"like":[84],"active-set":[86],"methods.":[87],"Both":[88],"primal":[89],"dual":[91],"residuals":[92],"enforced":[95],"down":[96],"strict":[98],"tolerances":[99],"otherwise":[101],"infeasibility":[102],"detected":[105],"from":[106],"intermediate":[107],"iterates.":[108],"A":[109],"C":[110],"implementation":[111],"proposed":[114],"is":[116],"tested":[117],"benchmarked":[119],"against":[120,137],"other":[121],"state-of-the-art":[122],"QP":[123],"solvers":[124],"large":[127],"variety":[128],"problem":[130],"data":[131],"shown":[133],"compare":[135],"favorably":[136],"these":[138],"solvers.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2019-11-22T00:00:00"}