New decision-making methods for ranking of non-dominated points for multi-objective optimization problems

A Multi-objective Optimization Problem (MOP) is a simultaneous optimization of more than one real-valued conflicting objective function subject to some constraints. Most MOP algorithms try to provide a set of Pareto optimal solutions that are equally good in terms of the objective functions. The set...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Scientia Iranica. Transaction E, Industrial engineering Ročník 31; číslo 3; s. 252 - 268
Hlavní autori: Dolatnezhadsomarin, A, Khorram, E, Yousefikhoshbakht, M
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Tehran Sharif University of Technology 01.06.2024
Predmet:
Algorithms
Decision analysis
Decision making
Familiarity
Hierarchies
Multiple objective analysis
Objective function
Optimization
Pareto optimization
Pareto optimum
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract A Multi-objective Optimization Problem (MOP) is a simultaneous optimization of more than one real-valued conflicting objective function subject to some constraints. Most MOP algorithms try to provide a set of Pareto optimal solutions that are equally good in terms of the objective functions. The set can be infinite, and hence, the analysis and choice task of one or several solutions among the equally good solutions is hard for a Decision Maker (DM). In this paper, a new scalarization approach is proposed to select a Pareto optimal solution for convex MOPs such that the relative importance assigned to its objective functions is very close together. In addition, two decision-making methods are developed to analyze convex and non-convex MOPs based on evaluating a set of Pareto optimal solutions and the relative importance of the objective functions. These methods support the DM to rank the solutions and obtain one or several of them for real implementation without having any familiarity with MOPs.
AbstractList A Multi-objective Optimization Problem (MOP) is a simultaneous optimization of more than one real-valued conflicting objective function subject to some constraints. Most MOP algorithms try to provide a set of Pareto optimal solutions that are equally good in terms of the objective functions. The set can be infinite, and hence, the analysis and choice task of one or several solutions among the equally good solutions is hard for a Decision Maker (DM). In this paper, a new scalarization approach is proposed to select a Pareto optimal solution for convex MOPs such that the relative importance assigned to its objective functions is very close together. In addition, two decision-making methods are developed to analyze convex and non-convex MOPs based on evaluating a set of Pareto optimal solutions and the relative importance of the objective functions. These methods support the DM to rank the solutions and obtain one or several of them for real implementation without having any familiarity with MOPs.
Author Khorram, E
Dolatnezhadsomarin, A
Yousefikhoshbakht, M
Author_xml – sequence: 1
  givenname: A
  surname: Dolatnezhadsomarin
  fullname: Dolatnezhadsomarin, A
– sequence: 2
  givenname: E
  surname: Khorram
  fullname: Khorram, E
– sequence: 3
  givenname: M
  surname: Yousefikhoshbakht
  fullname: Yousefikhoshbakht, M
BookMark eNotkE1LxDAYhHNQUNf9Bx4CnlvfJm0-jrL4sbDoZe9Lmr7R1G1Sm1TBX29xncvAMMwDc0XOQgxIyE0FJasZwF2yvmTAWNlIEKpsoFYXZJ1SD4tqzbjQl8S_4Dft0PrkYygG8-HDGx0wv8cuURcnOpnwl0VHF0DRxcEHk7GjY_QhnzrDfMy-iG2PNvsvpHHMfvA_Ji-bdJxie8QhXZNzZ44J1_--IvvHh_3mudi9Pm0397ti1CoXtagcx9ogKKtBSakFONVUleFtY0XLnHSt1gadtdKxTgnJoEYjmJCgW85X5PY0u3A_Z0z50Md5CgvxwGH5hQsQgv8Cc4dbEg
ContentType Journal Article
Copyright Copyright Sharif University of Technology 2024
Copyright_xml – notice: Copyright Sharif University of Technology 2024
DBID 3V.
7XB
8AF
8FE
8FG
8FK
8G5
AAFGM
AAMXL
ABJCF
ABQRF
ABRGS
ABUWG
ADZZV
AEEYA
AEUYN
AFKRA
AFLLJ
AFOLM
AGAJT
AQTIP
ATCPS
AZQEC
BENPR
BGLVJ
BHPHI
CCPQU
CWDGH
DWQXO
GNUQQ
GUQSH
HCIFZ
L6V
M2O
M7S
MBDVC
PATMY
PHGZM
PHGZT
PKEHL
PQCXX
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PRLXX
PTHSS
PYCSY
Q9U
SQOEQ
DOI 10.24200/sci.2022.57068.5048
DatabaseName ProQuest Central (Corporate)
ProQuest Central (purchase pre-March 2016)
STEM Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central (Alumni) (purchase pre-March 2016)
Research Library
ProQuest Central Korea - hybrid linking
Natural Science Collection - hybrid linking
Materials Science & Engineering Collection
Technology Collection - hybrid linking
Materials Science & Engineering Collection - hybrid linking
ProQuest Central (Alumni)
ProQuest Central (Alumni) - hybrid linking
Environmental Science Collection - hybrid linking
ProQuest One Sustainability
ProQuest Central UK/Ireland
SciTech Premium Collection - hybrid linking
ProQuest Central Student - hybrid linking
ProQuest Central Essentials - hybrid linking
ProQuest Women's & Gender Studies - hybrid linking
Agricultural & Environmental Science Collection
ProQuest Central Essentials
ProQuest Central
Technology collection
Natural Science Collection
ProQuest One
Middle East & Africa Database
ProQuest Central
ProQuest Central Student
Research Library Prep
SciTech Premium Collection
ProQuest Engineering Collection
Research Library
ProQuest Engineering Database
Research Library (Corporate)
Environmental Science Database
ProQuest Central Premium
ProQuest One Academic
ProQuest One Academic Middle East (New)
ProQuest Central - hybrid linking
ProQuest One Academic Eastern Edition (DO NOT USE)
One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
Research Library - hybrid linking
Engineering collection
Environmental Science Collection
ProQuest Central Basic
ProQuest One Sustainability - hybrid linking
DatabaseTitle Research Library Prep
ProQuest Central Student
Technology Collection
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest AP Science
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
Research Library (Alumni Edition)
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest One Sustainability
ProQuest Engineering Collection
Middle East & Africa Database
Natural Science Collection
ProQuest Central Korea
Agricultural & Environmental Science Collection
ProQuest Research Library
ProQuest Central (New)
Engineering Collection
Engineering Database
ProQuest Central Basic
ProQuest One Academic Eastern Edition
ProQuest Technology Collection
ProQuest SciTech Collection
Environmental Science Collection
ProQuest One Academic UKI Edition
Materials Science & Engineering Collection
Environmental Science Database
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
DatabaseTitleList Research Library Prep
Database_xml – sequence: 1
  dbid: BENPR
  name: ProQuest Central Collection
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EndPage 268
GroupedDBID -~X
3V.
7XB
7XC
8AF
8FE
8FG
8FH
8FK
8G5
8R4
8R5
ABJCF
ABUWG
ACIWK
ADFRT
AEUYN
AFKRA
AFRAH
AFWDF
ALMA_UNASSIGNED_HOLDINGS
ATCPS
AZQEC
BENPR
BGLVJ
BHPHI
BPHCQ
CCPQU
CWDGH
DWQXO
GNUQQ
GUQSH
HCIFZ
L6V
M2O
M7S
MBDVC
PATMY
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PROAC
PTHSS
PYCSY
Q2X
Q9U
UNMZH
~ZZ
ID FETCH-LOGICAL-p98t-461f3e4ae08c90877960f8511a3b5c6b2f7fb99aefcc7f2d867204ea626709b33
IEDL.DBID BENPR
IngestDate Mon Jun 30 09:07:26 EDT 2025
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-p98t-461f3e4ae08c90877960f8511a3b5c6b2f7fb99aefcc7f2d867204ea626709b33
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
PQID 3042036066
PQPubID 54704
PageCount 17
ParticipantIDs proquest_journals_3042036066
PublicationCentury 2000
PublicationDate 20240601
PublicationDateYYYYMMDD 2024-06-01
PublicationDate_xml – month: 06
  year: 2024
  text: 20240601
  day: 01
PublicationDecade 2020
PublicationPlace Tehran
PublicationPlace_xml – name: Tehran
PublicationTitle Scientia Iranica. Transaction E, Industrial engineering
PublicationYear 2024
Publisher Sharif University of Technology
Publisher_xml – name: Sharif University of Technology
SSID ssj0000492369
Score 2.322946
Snippet A Multi-objective Optimization Problem (MOP) is a simultaneous optimization of more than one real-valued conflicting objective function subject to some...
SourceID proquest
SourceType Aggregation Database
StartPage 252
SubjectTerms Algorithms
Decision analysis
Decision making
Familiarity
Hierarchies
Multiple objective analysis
Objective function
Optimization
Pareto optimization
Pareto optimum
Title New decision-making methods for ranking of non-dominated points for multi-objective optimization problems
URI https://www.proquest.com/docview/3042036066
Volume 31
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVPQU
  databaseName: Environmental Science Database
  databaseCode: PATMY
  dateStart: 20090601
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: http://search.proquest.com/environmentalscience
  omitProxy: false
  ssIdentifier: ssj0000492369
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Middle East & Africa Database
  databaseCode: CWDGH
  dateStart: 20090601
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: https://search.proquest.com/middleeastafrica
  omitProxy: false
  ssIdentifier: ssj0000492369
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central Collection
  databaseCode: BENPR
  dateStart: 20090601
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: https://www.proquest.com/central
  omitProxy: false
  ssIdentifier: ssj0000492369
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Engineering Database
  databaseCode: M7S
  dateStart: 20090601
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: http://search.proquest.com
  omitProxy: false
  ssIdentifier: ssj0000492369
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Research Library
  databaseCode: M2O
  dateStart: 20090601
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: https://search.proquest.com/pqrl
  omitProxy: false
  ssIdentifier: ssj0000492369
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07T8MwELagZYCBN-JRKg-sLiF2_JhQQa0YaKmgQmWq4kekIrUpTeH3c05cQEJiYcng3GDZyXff2Xf3IXRhhObcyIRIyyhhibJEW6pJqozylY3ClGoNz_ei35ejkRqEA7cipFWuMLEEapsbf0Z-6cNuQFvwkNfzN-JVo_ztapDQWEd136mM1VD9ptMfPH6dskS-_xhXVc0ceKMo8uUyEBbGcSsREZetJGLyFw6XzqW7899p7aLtQCtxu_oO9tCam-2jrR_NBg_QBPAM2yCpQ6alChWuBKQLDNQVe_l2P5ZneAYWNvdZMkBI8TyfzJaVTZl_SHL9WuEkzgFxpqGUEwdxmuIQDbud4e0dCUILZK7kkjB-lVHHUhdJo3yDQIhqMs_EUqoTw3WciUwrlbrMGJHFVnKvbONSiIVEpDSlR6gG83LHCDtOU-CcYMIFc7FVprxIFZYmQDWtPkGN1TKOw89SjL_X8PTv12doE3aOVZlaDVRbLt7dOdowH8tJsWiGvW-i9V784J_iCcYG7WHv5RPMqL8R
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V25TsNAEB2FQwIKbsQRYAugWzA-9igoEFcQIaKIgC7yHpaClDjgAOKj-Edm7Q0gIdFR0NpT2J7xm7ezM_sAdjRXjGmRUGHiiMaJNFSZSNFUaukmG7ku1Rpum7zVEvf38qYG76NZGNdWOcLEEqhNrl2N_MAtuxFtMUP6Dsor-_aK67Pi6PIUnbkbhudn7ZMG9RICdCDFkMbsMItsnNpAaOmOvkO-njmOkUYq0UyFGc-UlKnNtOZZaARzmi02RZbPA6lcsTPcGzxSJ1LlNnO9YscYTAgmBf5QEyd3pxeNz6JO4I47Y7Ia0cPkFwRuOgdXoWG4n_CAif0kiMUP2C9z2fncP_sK8zDrSTM5rqJ8AWq2vwgz345SXIIuojUxXjCI9kqNLVLJYxcEiTlx4vTuWp6RPlqY3PUAId0mg7zbH1Y2ZXclzdVDlQVIjnja84OqxEvvFMvQ_ou3X4FxfC67CsSyKEVGjSaMxzY0UpfbxNxECRJpo9agPvJax0NB0fly2frvt7dhqtG-bnaal62rDZjGoImrnrQ6jA-fnu0mTOqXYbd42vJhR6Dzx17_ADwpF3M
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LS8NAEB6kiujBt_h2D3rcNuaxmz2IiLW2WEoPRXsL2UegQptqquJP8985m4cKgjcPXjd7SDLDN9_szswHcKK4ZEyFAQ2171E_EJpK7UkaCyVsZyNXuVrDXZf3euFwKPpz8F71wtiyygoTc6DWqbJn5A2bdiPaYoRsJGVZRL_Zupg-UqsgZW9aKzmNwkVuzdsrpm_ZeaeJtj513db14KpNS4UBOhXhjPrsLPGMHxsnVMJOxkM6n1gKEnsyUEy6CU-kELFJlOKJq0NmJV1MjEkAd4S0Z6GI_vO47AU1mL-6b960Pw94HDv6jImiXQ8DoePYTh3MSF23HnCHhfXA8cMfISCPa63Vf_xH1mClJNPksvD-dZgzkw1Y_jZicRNGiOJEl0JCdJxrb5FCNjsjSNiJFa23a2lCJrhDp7Y2CGk4maajyazYk1dd0lQ-FNGBpIiz47KBlZSSPNkWDP7iU7ehhu9ldoAY5sXItHEL475xtVD59THXXoAEW8tdOKgsGJUQkUVf5tv7_fExLKJdo26nd7sPS-g_flGqdgC12dOzOYQF9TIbZU9HpQcSiP7Ywh-hryAp
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=article&rft.atitle=New+decision-making+methods+for+ranking+of+non-dominated+points+for+multi-objective+optimization+problems&rft.jtitle=Scientia+Iranica.+Transaction+E%2C+Industrial+engineering&rft.au=Dolatnezhadsomarin%2C+A&rft.au=Khorram%2C+E&rft.au=Yousefikhoshbakht%2C+M&rft.date=2024-06-01&rft.pub=Sharif+University+of+Technology&rft.volume=31&rft.issue=3&rft.spage=252&rft.epage=268&rft_id=info:doi/10.24200%2Fsci.2022.57068.5048&rft.externalDBID=HAS_PDF_LINK