Adaptive ∈-ranking on MNK-Landscapes

This work proposes an adaptive isin-ranking method to enhance Pareto based selection, aiming to develop effective many objective evolutionary optimization algorithm. isin-ranking fine grains ranking of solutions after they have been ranked by Pareto dominance, using a randomized sampling procedure c...

Full description

Saved in:
Bibliographic Details
Published in:2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making pp. 104 - 111
Main Authors: Aguirre, H., Tanaka, K.
Format: Conference Proceeding
Language:English
Japanese
Published: IEEE 01.03.2009
Subjects:
Pareto optimization
Sampling methods
ISBN:1424427649, 9781424427642
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract This work proposes an adaptive isin-ranking method to enhance Pareto based selection, aiming to develop effective many objective evolutionary optimization algorithm. isin-ranking fine grains ranking of solutions after they have been ranked by Pareto dominance, using a randomized sampling procedure combined with isin-dominance to favor a good distribution of the samples. In essence, sampled solutions keep their initial rank and solutions located within the virtually expanded dominance regions of the sampled solutions are demoted to an inferior rank. The parameter isin that determines the expanded regions of dominance of the sampled solutions is adapted to each generation so that the number of highest ranked solutions is kept close to a desired number expressed as a fraction of the population size. We enhanced NSGA-II with the proposed method and verify its performance on MNK-Landscapes. Experimented results show that the adaptive method works effectively and that convergence and diversity of the solutions found can improve remarkably on MNK-Landscapes with 3 les M les 10 objectives.
AbstractList This work proposes an adaptive isin-ranking method to enhance Pareto based selection, aiming to develop effective many objective evolutionary optimization algorithm. isin-ranking fine grains ranking of solutions after they have been ranked by Pareto dominance, using a randomized sampling procedure combined with isin-dominance to favor a good distribution of the samples. In essence, sampled solutions keep their initial rank and solutions located within the virtually expanded dominance regions of the sampled solutions are demoted to an inferior rank. The parameter isin that determines the expanded regions of dominance of the sampled solutions is adapted to each generation so that the number of highest ranked solutions is kept close to a desired number expressed as a fraction of the population size. We enhanced NSGA-II with the proposed method and verify its performance on MNK-Landscapes. Experimented results show that the adaptive method works effectively and that convergence and diversity of the solutions found can improve remarkably on MNK-Landscapes with 3 les M les 10 objectives.
Author Aguirre, H.
Tanaka, K.
Author_xml – sequence: 1
  givenname: H.
  surname: Aguirre
  fullname: Aguirre, H.
  organization: Fiber-Nanotech Young Researcher Empowerment Program |, Shinshu Univ., Nagano
– sequence: 2
  givenname: K.
  surname: Tanaka
  fullname: Tanaka, K.
  organization: Fac. of Eng., Shinshu Univ., Nagano
BookMark eNotj8tKw0AUhge0oKl9AHGTlbvEuZxMzixLvGKiG12Xk5kTiZdpSIrQN-hz-iQW2n_zLT744E_EaVxHFuJSyVwp6W6a6rbJtZQuB2cQTXEiEgUaQJcW3Ewke4dOWkA8E4tp-pT7QaHR6nNxvQw0bPpfTv92u2yk-NXHj3Qd0-blOasphsnTwNOFmHX0PfHiyLl4v797qx6z-vXhqVrWWa8Ku8lKpU3AFjwQoTXMQVLhPRQBkY0FrTDo0LXOabZalZJMS8q3FktubefNXFwduj0zr4ax_6Fxuzr-Mv-T-EJs
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/MCDM.2009.4938835
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE/IET Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EndPage 111
ExternalDocumentID 4938835
Genre orig-research
GroupedDBID 6IE
6IF
6IK
6IL
6IN
AAJGR
AARBI
AAWTH
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
IERZE
OCL
RIE
RIL
ID FETCH-LOGICAL-i156t-7123d8b4c4aa863eed0a5cc45d88e364218d2dfb992e62170a3ba1cb687eb6fc3
IEDL.DBID RIE
ISBN 1424427649
9781424427642
IngestDate Wed Aug 27 01:43:59 EDT 2025
IsPeerReviewed false
IsScholarly false
LCCN 2008906488
Language English
Japanese
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i156t-7123d8b4c4aa863eed0a5cc45d88e364218d2dfb992e62170a3ba1cb687eb6fc3
PageCount 8
ParticipantIDs ieee_primary_4938835
PublicationCentury 2000
PublicationDate 2009-03
PublicationDateYYYYMMDD 2009-03-01
PublicationDate_xml – month: 03
  year: 2009
  text: 2009-03
PublicationDecade 2000
PublicationTitle 2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making
PublicationTitleAbbrev MCDM
PublicationYear 2009
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0000452862
Score 1.4564117
Snippet This work proposes an adaptive isin-ranking method to enhance Pareto based selection, aiming to develop effective many objective evolutionary optimization...
SourceID ieee
SourceType Publisher
StartPage 104
SubjectTerms Pareto optimization
Sampling methods
Title Adaptive ∈-ranking on MNK-Landscapes
URI https://ieeexplore.ieee.org/document/4938835
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEB7a4sGTSiu-2YN4Mnazm-ZxlGoR7JYeFHorecxCL9vS12_o7_SXmOxuK4IXb3lASJiQmcnM9w3AvaMUueOGoL8MhGFSxncdUXls_A2TQmHJrj8Uo5GcTNS4AY8HLAwilsln-BSaZSzfze0mfJV1mUqltxia0BSCV1itw39KoAb31vkeu5UIztSe0qnuJ3VUk8aqm_Vfsoqtsl70V3WVUrkMTv63rVPo_KD0ovFB_5xBA4s2PDw7vQhPWPS125FQkd3PRfMiykbvZBhwvSHjadWBz8HrR_-N1LUQyMx7WGsivIZx0jDLtJY89SvHumct6zkpMQ1oVekSlxulEuTezYh1ajS1hstQ9CS36Tm0inmBFxAJqpiXTk4RAzONVjIXwlguKU9QOXcJ7XDG6aKiu5jWx7v6e_gajqsAS0jLuoHWernBWziy2_VstbwrZfQNXe6NuQ
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEB5qFfSk0opv9yCejN3spnkcpVoq3V16qNBb2U1mwcu29OFv6O_0l5jsbiuCF295QEiYkJnJzPcNwL2hFLnhGUF7GQjDoIzvGqJyP7M3TAqFJbt-JJJETiZq1IDHHRYGEcvkM3xyzTKWb2Z67b7KOkyF0loMe7DfZSzwK7TW7kfFkYNb-3yL3goEZ2pL6lT3gzquSX3ViXsvccVXWS_7q75KqV76x__b2Am0f3B63mingU6hgUULHp5NOnePmPe12RBXk93OebPCi5MhiRyy1-U8Ldvw3n8d9wakroZAPqyPtSLC6hgjM6ZZmkoe2pX9tKs16xopMXR4VWkCk2dKBcito-GnYZZSnXHpyp7kOjyDZjEr8Bw8QRWz8skpouOmSZXMhcg0l5QHqIy5gJY743ReEV5M6-Nd_j18B4eDcRxNo7dkeAVHVbjFJWldQ3O1WOMNHOjP1cdycVvK6xv1KZEA
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=2009+IEEE+Symposium+on+Computational+Intelligence+in+Multi-Criteria+Decision-Making&rft.atitle=Adaptive+%E2%88%88-ranking+on+MNK-Landscapes&rft.au=Aguirre%2C+H.&rft.au=Tanaka%2C+K.&rft.date=2009-03-01&rft.pub=IEEE&rft.isbn=9781424427642&rft.spage=104&rft.epage=111&rft_id=info:doi/10.1109%2FMCDM.2009.4938835&rft.externalDocID=4938835
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424427642/lc.gif&client=summon&freeimage=true
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424427642/mc.gif&client=summon&freeimage=true
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424427642/sc.gif&client=summon&freeimage=true