{"id":"https://openalex.org/W2510384539","doi":"https://doi.org/10.1109/tac.2017.2731817","title":"Weakly Coupled Dynamic Program: Information and Lagrangian Relaxations","display_name":"Weakly Coupled Dynamic Program: Information and Lagrangian Relaxations","publication_year":2017,"publication_date":"2017-07-25","ids":{"openalex":"https://openalex.org/W2510384539","doi":"https://doi.org/10.1109/tac.2017.2731817","mag":"2510384539"},"language":"en","primary_location":{"id":"doi:10.1109/tac.2017.2731817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2017.2731817","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","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/A5100405475","display_name":"Fan Ye","orcid":"https://orcid.org/0000-0001-7620-0875"},"institutions":[{"id":"https://openalex.org/I2802755631","display_name":"Morgan Stanley (United States)","ror":"https://ror.org/00aphdz18","country_code":"US","type":"company","lineage":["https://openalex.org/I2802755631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan Ye","raw_affiliation_strings":["Morgan Stanley, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-7620-0875","affiliations":[{"raw_affiliation_string":"Morgan Stanley, New York, NY, USA","institution_ids":["https://openalex.org/I2802755631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071590581","display_name":"Helin Zhu","orcid":"https://orcid.org/0000-0003-4106-6367"},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Helin Zhu","raw_affiliation_strings":["Uber, San Francisco, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4106-6367","affiliations":[{"raw_affiliation_string":"Uber, San Francisco, CA, USA","institution_ids":["https://openalex.org/I2946016260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083807807","display_name":"Enlu Zhou","orcid":"https://orcid.org/0000-0001-5399-6508"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Enlu Zhou","raw_affiliation_strings":["School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5399-6508","affiliations":[{"raw_affiliation_string":"School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6873,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.90062112,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"63","issue":"3","first_page":"698","last_page":"713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9988999962806702,"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/T11182","display_name":"Auction Theory and Applications","score":0.9988999962806702,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.998199999332428,"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/T10328","display_name":"Supply Chain and Inventory Management","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lagrangian-relaxation","display_name":"Lagrangian relaxation","score":0.8620051145553589},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.710671067237854},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6676459908485413},{"id":"https://openalex.org/keywords/lagrangian","display_name":"Lagrangian","score":0.6375223994255066},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.6274218559265137},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5967836380004883},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5290647745132446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5199976563453674},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.5001823902130127},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4146377444267273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3766486644744873},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3016745448112488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09914770722389221},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06705287098884583}],"concepts":[{"id":"https://openalex.org/C91765299","wikidata":"https://www.wikidata.org/wiki/Q3424292","display_name":"Lagrangian relaxation","level":2,"score":0.8620051145553589},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.710671067237854},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6676459908485413},{"id":"https://openalex.org/C53469067","wikidata":"https://www.wikidata.org/wiki/Q505735","display_name":"Lagrangian","level":2,"score":0.6375223994255066},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.6274218559265137},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5967836380004883},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5290647745132446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5199976563453674},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.5001823902130127},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4146377444267273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3766486644744873},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3016745448112488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09914770722389221},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06705287098884583},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tac.2017.2731817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2017.2731817","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.749.4028","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.749.4028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1405.3363.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G7170988589","display_name":null,"funder_award_id":"YIP FA-9550-14-1-0059","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W601863383","https://openalex.org/W1490333206","https://openalex.org/W1669104078","https://openalex.org/W1745373831","https://openalex.org/W1838526237","https://openalex.org/W1969007958","https://openalex.org/W1992595998","https://openalex.org/W2007502743","https://openalex.org/W2038027425","https://openalex.org/W2040766536","https://openalex.org/W2044069028","https://openalex.org/W2056921512","https://openalex.org/W2061849203","https://openalex.org/W2072302356","https://openalex.org/W2085130871","https://openalex.org/W2098432798","https://openalex.org/W2106554316","https://openalex.org/W2124832196","https://openalex.org/W2124897406","https://openalex.org/W2127536498","https://openalex.org/W2131228644","https://openalex.org/W2142685445","https://openalex.org/W2144787803","https://openalex.org/W2151786492","https://openalex.org/W2154463167","https://openalex.org/W2156040550","https://openalex.org/W2172140255","https://openalex.org/W2278934889","https://openalex.org/W2542637644","https://openalex.org/W2739765463","https://openalex.org/W3125634603","https://openalex.org/W3143833270","https://openalex.org/W4247165901","https://openalex.org/W6695188462","https://openalex.org/W6729528033","https://openalex.org/W6741686464"],"related_works":["https://openalex.org/W2002102264","https://openalex.org/W4237964977","https://openalex.org/W2155100848","https://openalex.org/W2075228635","https://openalex.org/W3149469165","https://openalex.org/W4313484281","https://openalex.org/W181997498","https://openalex.org/W2027845496","https://openalex.org/W3126007678","https://openalex.org/W2616198151"],"abstract_inverted_index":{"The":[0],"\u201cweakly":[1],"coupled":[2,38],"dynamic":[3,39,48,70,139],"program\u201d":[4],"describes":[5],"a":[6,24,61,93,104,116,124,138],"broad":[7],"class":[8],"of":[9,26,35,67,128,131],"stochastic":[10,17],"optimization":[11],"problems":[12],"in":[13],"which":[14,59],"multiple":[15],"controlled":[16],"processes":[18],"evolve":[19],"independently":[20],"but":[21],"subject":[22],"to":[23,91],"set":[25],"linking":[27,53],"constraints":[28],"imposed":[29],"on":[30,63,88,109,137],"the":[31,36,52,56,64,68,74,79,85,89,129],"controls.":[32],"One":[33],"feature":[34],"weakly":[37],"program":[40],"is":[41],"that":[42,83],"it":[43,114],"decouples":[44],"into":[45],"lower":[46],"dimensional":[47],"programs":[49],"by":[50],"dualizing":[51],"constraint":[54,87],"via":[55],"Lagrangian":[57,75],"relaxation,":[58,111],"yields":[60],"bound":[62,119,126],"optimal":[65],"value":[66],"original":[69],"program.":[71],"Together":[72],"with":[73],"bound,":[76],"we":[77,101],"generalize":[78],"information":[80,110],"relaxation":[81],"approach":[82],"relaxes":[84],"nonanticipative":[86],"controls":[90],"obtain":[92],"tighter":[94],"dual":[95,118],"bound.":[96],"To":[97],"tackle":[98],"large-scale":[99],"problems,":[100],"further":[102],"propose":[103],"computationally":[105],"tractable":[106],"method":[107,136],"based":[108],"and":[112,120],"show":[113],"provides":[115],"valid":[117],"its":[121],"performance":[122],"has":[123],"uniform":[125],"regardless":[127],"number":[130],"subproblems.":[132],"We":[133],"demonstrate":[134],"our":[135],"product":[140],"promotion":[141],"problem.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
