Constrained Multi-Modal Multi-Objective Evolutionary Algorithm with Problem Transformation into Two-Objective Subproblems

Real-world optimization problems often have multi-ple conflicting objective functions to be optimized simultaneously. In some of them, there are different Pareto optimal solutions with the same objective function values. Those problems are called multi-modal multi-objective optimization problems (MM...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS) s. 1 - 6
Hlavní autoři: Tokusaka, Teruhiko, Masuyama, Naoki, Nojima, Yusuke
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 09.11.2024
Témata:
Constrained dominance principle
Constrained multi-modal multi-objective optimization problems
Constraint handling
Evolutionary computation
Linear programming
Multi-objective evolutionary algorithms
Optimization
Pareto optimization
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract Real-world optimization problems often have multi-ple conflicting objective functions to be optimized simultaneously. In some of them, there are different Pareto optimal solutions with the same objective function values. Those problems are called multi-modal multi-objective optimization problems (MMOPs). For MMOPs, we proposed a decomposition-based multi-modal multi-objective evolutionary algorithm called MM2T in our previous study. However, MM2T does not consider constraints and thus cannot solve constrained MMOPs (CMMOPs). To apply MM2T to CMMOPs, we introduce the constrained dominance principle (CDP) into MM2T. We examine the search performance of MM2T with CDP through computational experiments.
AbstractList Real-world optimization problems often have multi-ple conflicting objective functions to be optimized simultaneously. In some of them, there are different Pareto optimal solutions with the same objective function values. Those problems are called multi-modal multi-objective optimization problems (MMOPs). For MMOPs, we proposed a decomposition-based multi-modal multi-objective evolutionary algorithm called MM2T in our previous study. However, MM2T does not consider constraints and thus cannot solve constrained MMOPs (CMMOPs). To apply MM2T to CMMOPs, we introduce the constrained dominance principle (CDP) into MM2T. We examine the search performance of MM2T with CDP through computational experiments.
Author Masuyama, Naoki
Tokusaka, Teruhiko
Nojima, Yusuke
Author_xml – sequence: 1
  givenname: Teruhiko
  surname: Tokusaka
  fullname: Tokusaka, Teruhiko
  email: sc24892v@st.omu.ac.jp
  organization: Graduate School of Informatics, Osaka Metropolitan University,Osaka,Japan
– sequence: 2
  givenname: Naoki
  surname: Masuyama
  fullname: Masuyama, Naoki
  email: masuyama@omu.ac.jp
  organization: Graduate School of Informatics, Osaka Metropolitan University,Osaka,Japan
– sequence: 3
  givenname: Yusuke
  surname: Nojima
  fullname: Nojima, Yusuke
  email: nojima@omu.ac.jp
  organization: Graduate School of Informatics, Osaka Metropolitan University,Osaka,Japan
BookMark eNpNUMFqAjEUTKE9tNY_6CHQ89q8ZDcxR1lsKygW1p4lcd-2KbuJZKPi31fRQhmYmcMwMPNAbn3wSMgzsBEA0y9VOavOkMAgH3HG8xEwJRkofUOGWumxKJhQQgh-T45l8H2Kxnms6WLXJpctQm3aq1_aH9wkt0c63Yd2l1zwJh7ppP0K0aXvjh5OTD9isC12dBWN75sQO3MOUudToKtD-NdS7ez2Eu4fyV1j2h6HVx2Qz9fpqnzP5su3WTmZZw6UTBlHDrY2IO1YM93occ2tklZaIwUqkWNe5NYKi6CNZsXGQtFw0TAUJi8aDWJAni69DhHX2-i604L13yPiF0OJX7U
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/SCISISIS61014.2024.10760179
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE/IET Electronic Library
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9798350373332
EndPage 6
ExternalDocumentID 10760179
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i176t-2e21bda16b8909f98d2b76b6ba63e734e454bb3be19a905cb15f23f0e3a45f913
IEDL.DBID RIE
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001460285200187&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Jan 15 06:21:38 EST 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i176t-2e21bda16b8909f98d2b76b6ba63e734e454bb3be19a905cb15f23f0e3a45f913
PageCount 6
ParticipantIDs ieee_primary_10760179
PublicationCentury 2000
PublicationDate 2024-Nov.-9
PublicationDateYYYYMMDD 2024-11-09
PublicationDate_xml – month: 11
  year: 2024
  text: 2024-Nov.-9
  day: 09
PublicationDecade 2020
PublicationTitle 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS)
PublicationTitleAbbrev SCIS&ISIS
PublicationYear 2024
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.8885975
Snippet Real-world optimization problems often have multi-ple conflicting objective functions to be optimized simultaneously. In some of them, there are different...
SourceID ieee
SourceType Publisher
StartPage 1
SubjectTerms Constrained dominance principle
Constrained multi-modal multi-objective optimization problems
Constraint handling
Evolutionary computation
Linear programming
Multi-objective evolutionary algorithms
Optimization
Pareto optimization
Title Constrained Multi-Modal Multi-Objective Evolutionary Algorithm with Problem Transformation into Two-Objective Subproblems
URI https://ieeexplore.ieee.org/document/10760179
WOSCitedRecordID wos001460285200187&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/eLvHCXMwlV3NS8MwFA9uiHhSceI3Ab12tk2aNkcZG3pwDjZht5GXD63MVrpusv_eJq06Dx4klxDICyR57-W95JcfQteVYTSB4twzUhmPSqM9SDTxIm2TFoJLImuyiXg4TKZTPmrA6g4Lo7V2j89011bdXb7K5dKmyioNty84Yt5CrThmNVhrB101_2bejHv3Y1uY5Z-tQr-Qdr96_OJOca5jsPfPQfdR5weEh0ff7uUAbensEK0twaajddAKO_Cs95ArMW_qj_BaGzDcXzV7ShRrfDt_zou0fHnDNu1qpVoSGTzZOLTmGU6zMseTj3xDSmVWGsaZRQc9DfqT3p3XsCd4aRCz0gt1GIASAYOE-9zwRIUQM2AgGNExoZpGFICADrjgfiQhiExIjK-JoJHhATlC7SzP9DHCoCLlhwChUYKaKmCrtFYynwCApL4UJ6hj5232Xn-QMfuastM_2s_Qrl0dB-nj56hdFkt9gbblqkwXxaVb1k-uSamW
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA5aRT2pWPFtQK-pu5t95SilpcW2FrpCbyWTh67UXWm3lf57N7ur1oMHySUEMoE8ZjKT-fIhdJsrRm1LxogWUhNXaEUgVJR4ygQtOBNUlGQTwWAQjsdsWIHVCyyMUqpIPlMNUy3e8mUqFiZUlp9wk8ERsE205eWG1CrhWjvopvo5827U7I5M8Q0Dbe78OW7jq88v9pTCeLT3_znsAar_wPDw8NvAHKINlRyhlaHYLIgdlMQFfJb0U8mnVf0RXksVhlvLalfx2QrfT5_TWZy9vGETeDVSDY0MjtaurWmC4yRLcfSRrknJFUvFOTOvo6d2K2p2SMWfQGI78DPiKMcGyW0fQmYxzULpQOCDD9ynKqCucj0XgIKyGWeWJ8D2tEO1pSh3Pc1seoxqSZqoE4RBetJyABwtuatzly0_t8K3KAAI1xL8FNXNvE3eyy8yJl9TdvZH-zXa7UT93qTXHTycoz2zUgXAj12gWjZbqEu0LZZZPJ9dFUv8CbQWrOM
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%3Abook&rft.genre=proceeding&rft.title=2024+Joint+13th+International+Conference+on+Soft+Computing+and+Intelligent+Systems+and+25th+International+Symposium+on+Advanced+Intelligent+Systems+%28SCIS%26ISIS%29&rft.atitle=Constrained+Multi-Modal+Multi-Objective+Evolutionary+Algorithm+with+Problem+Transformation+into+Two-Objective+Subproblems&rft.au=Tokusaka%2C+Teruhiko&rft.au=Masuyama%2C+Naoki&rft.au=Nojima%2C+Yusuke&rft.date=2024-11-09&rft.pub=IEEE&rft.spage=1&rft.epage=6&rft_id=info:doi/10.1109%2FSCISISIS61014.2024.10760179&rft.externalDocID=10760179