Difficulty Controllable and Scalable Constrained Multi-objective Test Problems

In this paper, we propose a general toolkit to construct constrained multi-objective optimisation problems (CMOPs) with three different kinds of constraint functions. Based on this toolkit, we suggested eight constrained multi-objective optimisation problems named CMOP1-CMOP8. As the ratio of feasib...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2015 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration s. 76 - 83
Hlavní autoři: Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Kaiwen Hu, Haibin Yin
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.12.2015
Témata:
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract In this paper, we propose a general toolkit to construct constrained multi-objective optimisation problems (CMOPs) with three different kinds of constraint functions. Based on this toolkit, we suggested eight constrained multi-objective optimisation problems named CMOP1-CMOP8. As the ratio of feasible regions in the whole search space determines the difficulty of a constrained multi-objective optimisation problem, we propose four test instances CMOP3-6, which have very low ratio of feasible regions. To study the difficulties of proposed test instances, we make some experiments with two popular CMOEAs - MOEA/D-CDP and NSGA-II-CDP, and analysed their performances.
AbstractList In this paper, we propose a general toolkit to construct constrained multi-objective optimisation problems (CMOPs) with three different kinds of constraint functions. Based on this toolkit, we suggested eight constrained multi-objective optimisation problems named CMOP1-CMOP8. As the ratio of feasible regions in the whole search space determines the difficulty of a constrained multi-objective optimisation problem, we propose four test instances CMOP3-6, which have very low ratio of feasible regions. To study the difficulties of proposed test instances, we make some experiments with two popular CMOEAs - MOEA/D-CDP and NSGA-II-CDP, and analysed their performances.
Author Wenji Li
Haibin Yin
Zhun Fan
Xinye Cai
Hui Li
Kaiwen Hu
Author_xml – sequence: 1
  surname: Zhun Fan
  fullname: Zhun Fan
  organization: Dept. of Electron. Eng., Shantou Univ., Shantou, China
– sequence: 2
  surname: Wenji Li
  fullname: Wenji Li
  organization: Dept. of Electron. Eng., Shantou Univ., Shantou, China
– sequence: 3
  surname: Xinye Cai
  fullname: Xinye Cai
  organization: Coll. of Comput. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
– sequence: 4
  surname: Hui Li
  fullname: Hui Li
  organization: Dept. of Electron. Eng., Shantou Univ., Shantou, China
– sequence: 5
  surname: Kaiwen Hu
  fullname: Kaiwen Hu
  organization: Dept. of Electron. Eng., Shantou Univ., Shantou, China
– sequence: 6
  surname: Haibin Yin
  fullname: Haibin Yin
  organization: Sch. of Mech. & Electron. Eng., Wuhan Univ. of Technol. Wuhan, Wuhan, China
BookMark eNotjFtLxDAUhCMo6K77LviSP9B6cukmeZR6K6wXcH1ekvQEIt1Umijsv7eyMgPDMB-zIKdpTEjIFYOaMTA3Xdv9uebAmppBc0IWTK6V0IJxOCernKMDqVXDBMAFebmLIUT_PZQDbcdUpnEYrBuQ2tTTd2-PZV5ymWxM2NPnmY3V6D7Rl_iDdIu50LdpnLl9viRnwQ4ZV_-5JB8P99v2qdq8Pnbt7aaKHHSp0CrZBK9RBQ4QvJVWQnDBG5C9BaGR90EHNNJzw4xQjqP3yDxH7VSzFktyffyNiLj7muLeToedErOMEL8X9VAN
CODEN IEEPAD
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/ICIICII.2015.105
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 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 Computer Science
EISBN 1467383120
9781467383127
EndPage 83
ExternalDocumentID 7373793
Genre orig-research
GroupedDBID 6IE
6IL
ALMA_UNASSIGNED_HOLDINGS
CBEJK
RIB
RIC
RIE
RIL
ID FETCH-LOGICAL-i208t-ea745fc8e7f200fca4a40fbfc904da038e2df8fe94c291937b2ecce1c2e8b7563
IEDL.DBID RIE
ISICitedReferencesCount 5
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000380447500018&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Dec 20 05:18:33 EST 2023
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i208t-ea745fc8e7f200fca4a40fbfc904da038e2df8fe94c291937b2ecce1c2e8b7563
PageCount 8
ParticipantIDs ieee_primary_7373793
PublicationCentury 2000
PublicationDate 20151201
PublicationDateYYYYMMDD 2015-12-01
PublicationDate_xml – month: 12
  year: 2015
  text: 20151201
  day: 01
PublicationDecade 2010
PublicationTitle 2015 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration
PublicationTitleAbbrev ICIICII
PublicationYear 2015
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssib048751300
Score 1.6080767
Snippet In this paper, we propose a general toolkit to construct constrained multi-objective optimisation problems (CMOPs) with three different kinds of constraint...
SourceID ieee
SourceType Publisher
StartPage 76
SubjectTerms Aerospace electronics
Computer science
Constrained Multi-objective Evolutionary Algorithm
Constrained Multi-objective Optimisation problem
Evolutionary computation
Linear programming
Pareto optimization
Shape
Title Difficulty Controllable and Scalable Constrained Multi-objective Test Problems
URI https://ieeexplore.ieee.org/document/7373793
WOSCitedRecordID wos000380447500018&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/eLvHCXMwlV1LSwMxEB7a4sFT1VZ8k4NHY9Mk2yTnarEgpYcqvZVsHlCRrfQh-O_N7LYVwYtkD8kSCEyyO5PM9-UDuGXOe-Z4lzrNJJVROqplpmg3GpH3kg9ipRbB67MajfR0asY1uNtzYUIIJfgs3GO1zOX7hdvgUVlHiVSMqENdKVVxtXZrB-NuzMzsMpHMdIb9IT4I38pQzvaXfkrpPgbN_w18BO0fHh4Z7z3MMdRCcQLNnRAD2X6XLRg94MkLXqLxRfoV9vwdKVHEFj71slUDtTlLRYjgScm7pYv8rfrfkUlyDjgUisus2vAyeJz0n-hWKIHOOdNrGqySiMUKKqZFH52VVrKYR2eY9JYJHbiPOgYjHTcpYlM5TzMXuo4HnausJ06hUSyKcAaE96zwGbJNrZDWcWuTXfOYNi4pOHIqO4cWmmf2Ud2FMdta5uLv15dwiNav4B9X0FgvN-EaDtzner5a3pQT-A1SuJ35
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFH7MKehp6ib-tgePxqVpuqTn6dhwlh2m7DbS_ICJdLJ1gv-9ee02EbxIc2hKIfBemvea9335AG6pNoZqFhItKSfccU0kjwUJXRJlHR-DaKlF8DoUaSonk2RUg7stF8ZaW4LP7D3elrV8M9cr3Cpri8hfSbQDuzHnLKzYWpvZg5k31mY2tUiatAfdATYEcMUoaPtLQaUMIL3G_4Y-hNYPEy8YbWPMEdRsfgyNjRRDsP4ym5A-4N4LHqPxFXQr9Pk7kqIClRv_lqo6qM5ZakJYE5TMWzLP3qoVLxj78IBDobzMsgUvvcdxt0_WUglkxqgsiFWCIxrLCuenvdOKK05d5nRCuVE0kpYZJ51NuGaJz9lExrzvbKiZlZmIO9EJ1PN5bk8hYB0VmRj5piriSjOlvF0z539dfHqkRXwGTTTP9KM6DWO6tsz5349vYL8_fh5Oh4P06QIO0BMVGOQS6sViZa9gT38Ws-XiunTmN7cPoUA
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=2015+International+Conference+on+Industrial+Informatics+-+Computing+Technology%2C+Intelligent+Technology%2C+Industrial+Information+Integration&rft.atitle=Difficulty+Controllable+and+Scalable+Constrained+Multi-objective+Test+Problems&rft.au=Zhun+Fan&rft.au=Wenji+Li&rft.au=Xinye+Cai&rft.au=Hui+Li&rft.date=2015-12-01&rft.pub=IEEE&rft.spage=76&rft.epage=83&rft_id=info:doi/10.1109%2FICIICII.2015.105&rft.externalDocID=7373793