Analyzing the Effect of Persistent Asset Switches on a Class of Hybrid-Inspired Optimization Algorithms

Convex optimization challenges are currently pervasive in many science and engineering domains. In many applications of convex optimization, such as those involving multi-agent systems and resource allocation, the objective function can persistently switch during the execution of an optimization alg...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Proceedings of the American Control Conference s. 3422 - 3427
Hlavní autori: Baradaran, Matina, Le, Justin H., Teel, Andrew R.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: American Automatic Control Council 25.05.2021
Predmet:
ISSN:2378-5861
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract Convex optimization challenges are currently pervasive in many science and engineering domains. In many applications of convex optimization, such as those involving multi-agent systems and resource allocation, the objective function can persistently switch during the execution of an optimization algorithm. Motivated by such applications, we analyze the effect of persistently switching objectives in continuous-time optimization algorithms. In particular, we take advantage of existing robust stability results for switched systems with distinct equilibria and extend these results to systems described by differential inclusions, making the results applicable to recent optimization algorithms that employ differential inclusions for improving efficiency and/or robustness. Within the framework of hybrid systems theory, we provide an accurate characterization, in terms of Omega-limit sets, of the set to which the optimization dynamics converge. Finally, by considering the switching signal to be constrained in its average dwell time, we establish semi-global practical asymptotic stability of these sets with respect to the dwell-time parameter.
AbstractList Convex optimization challenges are currently pervasive in many science and engineering domains. In many applications of convex optimization, such as those involving multi-agent systems and resource allocation, the objective function can persistently switch during the execution of an optimization algorithm. Motivated by such applications, we analyze the effect of persistently switching objectives in continuous-time optimization algorithms. In particular, we take advantage of existing robust stability results for switched systems with distinct equilibria and extend these results to systems described by differential inclusions, making the results applicable to recent optimization algorithms that employ differential inclusions for improving efficiency and/or robustness. Within the framework of hybrid systems theory, we provide an accurate characterization, in terms of Omega-limit sets, of the set to which the optimization dynamics converge. Finally, by considering the switching signal to be constrained in its average dwell time, we establish semi-global practical asymptotic stability of these sets with respect to the dwell-time parameter.
Author Baradaran, Matina
Teel, Andrew R.
Le, Justin H.
Author_xml – sequence: 1
  givenname: Matina
  surname: Baradaran
  fullname: Baradaran, Matina
  email: baradaranhosseini@ucsb.edu
  organization: University of California,Department of Electrical and Computer Engineering,Santa Barbara,CA,USA,93106
– sequence: 2
  givenname: Justin H.
  surname: Le
  fullname: Le, Justin H.
  email: justinle@ucsb.edu
  organization: University of California,Department of Electrical and Computer Engineering,Santa Barbara,CA,USA,93106
– sequence: 3
  givenname: Andrew R.
  surname: Teel
  fullname: Teel, Andrew R.
  email: teel@ucsb.edu
  organization: University of California,Department of Electrical and Computer Engineering,Santa Barbara,CA,USA,93106
BookMark eNotkNFKwzAYRqMo6KZPIEheoDN_0iTNZSnTDQYT1OuRJn-3SJeOJiDb0ztxV-e7OHwXZ0Ju4hCRkGdgMy4MmJe6aSSTADPOOMxMWXED8opMQClZlmC0uib3XOiqkJWCOzJJ6ZsxMEaxe7Kto-2PpxC3NO-QzrsOXaZDR99xTCFljJnWKWGmHz8hux0mOkRqadPblP68xbEdgy-WMR3CiJ6uDznsw8nmcPbqfjuMIe_26YHcdrZP-HjhlHy9zj-bRbFavy2belUEzkQuULcgna60F15Aa433qtQKWi5c69B2mlnBS3GezjivmLbOVlYxIVXpUIgpefr_DYi4OYxhb8fj5hJF_AKuxVqh
ContentType Conference Proceeding
DBID 6IE
6IH
CBEJK
RIE
RIO
DOI 10.23919/ACC50511.2021.9482915
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan (POP) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP) 1998-present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISBN 1665441976
9781665441971
EISSN 2378-5861
EndPage 3427
ExternalDocumentID 9482915
Genre orig-research
GrantInformation_xml – fundername: AFOSR
  grantid: FA9550-18-1-0246
  funderid: 10.13039/100000181
GroupedDBID -~X
23M
6IE
6IF
6IH
6IK
6IL
6IM
6IN
AAJGR
AAWTH
ABLEC
ACGFS
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IEGSK
IJVOP
IPLJI
M43
OCL
RIE
RIL
RIO
RNS
ID FETCH-LOGICAL-i203t-e7b15c787d3d31ba9dd64761b23cbceaf70a3243ceac9cd607aca8a603564ce33
IEDL.DBID RIE
ISICitedReferencesCount 1
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000702263303080&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Aug 27 02:39:49 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i203t-e7b15c787d3d31ba9dd64761b23cbceaf70a3243ceac9cd607aca8a603564ce33
PageCount 6
ParticipantIDs ieee_primary_9482915
PublicationCentury 2000
PublicationDate 2021-May-25
PublicationDateYYYYMMDD 2021-05-25
PublicationDate_xml – month: 05
  year: 2021
  text: 2021-May-25
  day: 25
PublicationDecade 2020
PublicationTitle Proceedings of the American Control Conference
PublicationTitleAbbrev ACC
PublicationYear 2021
Publisher American Automatic Control Council
Publisher_xml – name: American Automatic Control Council
SSID ssj0019960
Score 1.7732652
Snippet Convex optimization challenges are currently pervasive in many science and engineering domains. In many applications of convex optimization, such as those...
SourceID ieee
SourceType Publisher
StartPage 3422
SubjectTerms Asymptotic stability
Convex functions
Heuristic algorithms
Linear programming
Robust stability
Switched systems
Switches
Title Analyzing the Effect of Persistent Asset Switches on a Class of Hybrid-Inspired Optimization Algorithms
URI https://ieeexplore.ieee.org/document/9482915
WOSCitedRecordID wos000702263303080&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1dS8MwFA1z-KAvfmziN3nw0W5t0ibN4xiOCTIHKuxt5Kuz4FrpOkV_vbltmQq--HYpDYWcNje3J-dchK5YnFgVavfyJtQVKIr5XswE9WziqiElI05shfQdn0zi2UxMW-h6o4Wx1laHz2wPworLN7lew6-yvghjIkBRvsU5q7VaG8YAXEZqBTChIhD9wXDoknsAJSAJes3IXy1Uqgwy2vvfs_dR91uKh6ebJHOAWjY7RLs_XAQ7aFEZi3y6GLvdHK79iHGeYDjdDihmJQZut8QP7ymAtMJ5hiWu-mHCfeMPkG15txmw7tbge7eMLBt9Jh68LPIiLZ-Xqy56Gt08Dsde0z_BS4lPS89yFUTafZGGGhooKYxhIWeBIlQrbWXCfen2U9SFWmjDfC61jCXzacRCbSk9Qu0sz-wxwsxGIpSCC6M0pD1FtBA6cmU55Ubx5AR1YMrmr7VFxryZrdO_L5-hHUAFSHgSnaN2WaztBdrWb2W6Ki4rXL8A_QamHA
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1dS8MwFA1DBfXFj038Ng8-2q1t2qR5HMOx4ZwDJ-xt5Kuz4FrZOkV_vbltmQq--HYpDYWcNje3J-dchK5pFBsZKPvyxsQWKJK6TkQ5cUxsqyEpQuabAukBGw6jyYSPauhmrYUxxhSHz0wTwoLL15lawa-yFg8in4OifBM6Z7mlWmvNGYDPSKkB9gn3eKvd6dj07kER6HvNauyvJipFDunu_e_p-6jxLcbDo3WaOUA1kx6i3R8-gnU0K6xFPm2M7X4Ol47EOIsxnG8HHNMcA7ub48f3BGBa4izFAhcdMeG-3gcIt5x-Cry70fjBLiTzSqGJ2y-zbJHkz_NlAz11b8ednlN1UHAS3yW5Y5j0QmW_SU008aTgWtOAUU_6REllRMxcYXdUxIaKK01dJpSIBHVJSANlCDlCG2mWmmOEqQl5IDjjWipIfNJXnKvQFuaEacniE1SHKZu-liYZ02q2Tv--fIW2e-P7wXTQH96doR1ACCh5PzxHG_liZS7QlnrLk-XissD4C8pNqWI
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=Proceedings+of+the+American+Control+Conference&rft.atitle=Analyzing+the+Effect+of+Persistent+Asset+Switches+on+a+Class+of+Hybrid-Inspired+Optimization+Algorithms&rft.au=Baradaran%2C+Matina&rft.au=Le%2C+Justin+H.&rft.au=Teel%2C+Andrew+R.&rft.date=2021-05-25&rft.pub=American+Automatic+Control+Council&rft.eissn=2378-5861&rft.spage=3422&rft.epage=3427&rft_id=info:doi/10.23919%2FACC50511.2021.9482915&rft.externalDocID=9482915