A Novel Multi-Objective Competitive Swarm Optimization Algorithm
In this article, a new algorithm, namely the multi-objective competitive swarm optimizer (MOCSO), is introduced to handle multi-objective problems. The algorithm has been principally motivated from the competitive swarm optimizer (CSO) and the NSGA-II algorithm. In MOCSO, a pair wise competitive sce...
Uloženo v:
| Vydáno v: | International journal of applied metaheuristic computing Ročník 11; číslo 4; s. 114 - 129 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Hershey
IGI Global
01.10.2020
|
| Témata: | |
| ISSN: | 1947-8283, 1947-8291 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | In this article, a new algorithm, namely the multi-objective competitive swarm optimizer (MOCSO), is introduced to handle multi-objective problems. The algorithm has been principally motivated from the competitive swarm optimizer (CSO) and the NSGA-II algorithm. In MOCSO, a pair wise competitive scenario is presented to achieve the dominance relationship between two particles in the population. In each pair wise competition, the particle that dominates the other particle is considered the winner and the other is consigned as the loser. The loser particles learn from the respective winner particles in each individual competition. The inspired CSO algorithm does not use any memory to remember the global best or personal best particles, hence, MOCSO does not need any external archive to store elite particles. The experimental results and statistical tests confirm the superiority of MOCSO over several state-of-the-art multi-objective algorithms in solving benchmark problems. |
|---|---|
| AbstractList | In this article, a new algorithm, namely the multi-objective competitive swarm optimizer (MOCSO), is introduced to handle multi-objective problems. The algorithm has been principally motivated from the competitive swarm optimizer (CSO) and the NSGA-II algorithm. In MOCSO, a pair wise competitive scenario is presented to achieve the dominance relationship between two particles in the population. In each pair wise competition, the particle that dominates the other particle is considered the winner and the other is consigned as the loser. The loser particles learn from the respective winner particles in each individual competition. The inspired CSO algorithm does not use any memory to remember the global best or personal best particles, hence, MOCSO does not need any external archive to store elite particles. The experimental results and statistical tests confirm the superiority of MOCSO over several state-of-the-art multi-objective algorithms in solving benchmark problems. |
| Audience | Academic |
| Author | Mohapatra, Prabhujit Roy, Santanu Das, Kedar Nath Dey, Nilanjan Kumar, Ram |
| AuthorAffiliation | Techno India College of Technology, West Bengal, India NIT Silchar, Silchar, India Katihar Engineering College, Katihar, India VIT University, Vellore, Tamilnadu, India |
| AuthorAffiliation_xml | – name: NIT Silchar, Silchar, India – name: Techno India College of Technology, West Bengal, India – name: Katihar Engineering College, Katihar, India – name: VIT University, Vellore, Tamilnadu, India |
| Author_xml | – sequence: 1 givenname: Nilanjan surname: Dey fullname: Dey, Nilanjan organization: Techno India College of Technology, West Bengal, India – sequence: 2 givenname: Ram surname: Kumar fullname: Kumar, Ram organization: Katihar Engineering College, Katihar, India – sequence: 3 givenname: Prabhujit surname: Mohapatra fullname: Mohapatra, Prabhujit organization: VIT University, Vellore, Tamilnadu, India – sequence: 4 givenname: Kedar surname: Das middlename: Nath fullname: Das, Kedar Nath organization: NIT Silchar, Silchar, India – sequence: 5 givenname: Santanu surname: Roy fullname: Roy, Santanu organization: NIT Silchar, Silchar, India |
| BookMark | eNp9kc1PwyAYxonRxKm7e2zixYOd0EJLbzaLTo26g3om0NKOpV8CndG_XuzMliwqEHgPv-d9yfMcgf2mbSQApwhOMET08u4-fZxOAhhABN2J9sAIJTj2aZCg_U1Nw0MwNmYJ3SI4jiEZgavUe2pXsvIe-8oqfy6WMrNqJb1pW3fSqqF-fue69uadVbX65Fa1jZdWZauVXdQn4KDglZHjn_cYvN5cv0xv_Yf57G6aPvgZhsT6OeUYCVpw7KqARCiLcR5CJGIpiBBQ5iigMSwIDCkWRZaIGOWYJHkgokRAER6Ds3XfTrdvvTSWLdteN24kC5IQ0QiHEXHUxZoqeSWZ6I1qpHGXUeXCmpL3xrA0JknkNqEOh2s8060xWhas06rm-oMhyL6dZYOzbOusk0Q7kkzZwROruar-E56vhapU27_vYqzLC4fOfkFdSmxIiW1SYkNKf41EKPwC3SGhzQ |
| CitedBy_id | crossref_primary_10_1038_s41598_024_60821_0 crossref_primary_10_1016_j_swevo_2024_101543 |
| Cites_doi | 10.1007/978-3-540-31880-4_4 10.1109/TEVC.2007.892759 10.1109/TEVC.2005.861417 10.1109/CEC.2001.934295 10.1007/978-3-540-31880-4_35 10.1109/MCI.2017.2742868 10.1016/j.ins.2017.10.037 10.1162/106365600568202 10.1016/j.ejor.2015.06.071 10.1145/2001576.2001587 10.1109/TCYB.2014.2322602 10.1109/TEVC.2007.894202 10.1109/ICNN.1995.488968 10.1109/CEC.2006.1688406 10.1109/4235.585893 10.1162/EVCO_a_00009 10.1016/j.ins.2015.07.018 10.1109/MCDM.2009.4938830 10.1007/s40747-017-0057-5 10.1109/4235.996017 10.1109/TEVC.2013.2281525 10.1016/j.amc.2014.12.006 10.1109/CEC.2002.1004388 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2020 IGI Global Copyright IGI Global 2020 |
| Copyright_xml | – notice: COPYRIGHT 2020 IGI Global – notice: Copyright IGI Global 2020 |
| DBID | AAYXX CITATION N95 7SC 8FD 8FE 8FG AFKRA ARAPS AZQEC BENPR BGLVJ CCPQU DWQXO GNUQQ HCIFZ JQ2 K7- L7M L~C L~D P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS |
| DOI | 10.4018/IJAMC.2020100106 |
| DatabaseName | CrossRef Gale Business: Insights Computer and Information Systems Abstracts Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central ProQuest Technology Collection ProQuest One Community College ProQuest Central ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database (ProQuest) Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China |
| DatabaseTitle | CrossRef Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Central Korea ProQuest Central (New) Advanced Technologies Database with Aerospace Advanced Technologies & Aerospace Collection ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection Computer and Information Systems Abstracts Professional ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) |
| DatabaseTitleList | CrossRef Computer Science Database |
| Database_xml | – sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1947-8291 |
| EndPage | 129 |
| ExternalDocumentID | A759696958 10_4018_IJAMC_2020100106 vel_Multi_Objective_Compe10_4018_IJAMC_202010010611 |
| GeographicLocations | India |
| GeographicLocations_xml | – name: India |
| GroupedDBID | 0R ABEPT ADEKF ALMA_UNASSIGNED_HOLDINGS COVLG EBS HZ JRD MV1 NEEBM O9- RIF 0R~ 4.4 AAYVP AAYXX ADMLS AFFHD AFKRA ARAPS BAAKF BENPR BGLVJ BYHXH CBWLS CCPQU CDTDJ CIGCI CITATION CKMBR CNQXE CTSEY H13 HCIFZ HZ~ IAO ICD ITC K7- N95 PHGZM PHGZT PQGLB 7SC 8FD 8FE 8FG AZQEC DWQXO EJD GNUQQ JQ2 L7M L~C L~D P62 PKEHL PQEST PQQKQ PQUKI PRINS |
| ID | FETCH-LOGICAL-c405t-d8a41b8fa4d8a2561c74d301b7eb5bb0ed12870f50384bfc9b71d459d2b69b0b3 |
| IEDL.DBID | K7- |
| ISICitedReferencesCount | 3 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000568375000006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1947-8283 |
| IngestDate | Sun Nov 09 07:02:56 EST 2025 Sat Nov 29 08:43:16 EST 2025 Sat Nov 29 02:52:00 EST 2025 Tue Nov 18 22:16:51 EST 2025 Tue Jan 05 23:29:30 EST 2021 Fri Jan 15 00:04:31 EST 2021 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c405t-d8a41b8fa4d8a2561c74d301b7eb5bb0ed12870f50384bfc9b71d459d2b69b0b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0001-8437-498X |
| PQID | 2931864365 |
| PQPubID | 2045863 |
| PageCount | 16 |
| ParticipantIDs | gale_businessinsightsgauss_A759696958 igi_journals_vel_Multi_Objective_Compe10_4018_IJAMC_202010010611 proquest_journals_2931864365 crossref_primary_10_4018_IJAMC_2020100106 crossref_citationtrail_10_4018_IJAMC_2020100106 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-10-01 |
| PublicationDateYYYYMMDD | 2020-10-01 |
| PublicationDate_xml | – month: 10 year: 2020 text: 2020-10-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Hershey |
| PublicationPlace_xml | – name: Hershey |
| PublicationTitle | International journal of applied metaheuristic computing |
| PublicationYear | 2020 |
| Publisher | IGI Global |
| Publisher_xml | – name: IGI Global |
| References | IJAMC.2020100106-26 IJAMC.2020100106-25 IJAMC.2020100106-24 IJAMC.2020100106-23 IJAMC.2020100106-22 K.Deb (IJAMC.2020100106-7) 2002 IJAMC.2020100106-21 IJAMC.2020100106-20 IJAMC.2020100106-1 IJAMC.2020100106-0 IJAMC.2020100106-15 IJAMC.2020100106-14 IJAMC.2020100106-13 IJAMC.2020100106-12 IJAMC.2020100106-11 IJAMC.2020100106-10 IJAMC.2020100106-5 IJAMC.2020100106-6 IJAMC.2020100106-3 IJAMC.2020100106-4 IJAMC.2020100106-9 IJAMC.2020100106-19 E.Zitzler (IJAMC.2020100106-28) 2001 IJAMC.2020100106-18 IJAMC.2020100106-17 D.Brockhoff (IJAMC.2020100106-2) 2007 IJAMC.2020100106-8 W.Peng (IJAMC.2020100106-16) 2008 E.Zitzler (IJAMC.2020100106-27) 2004 |
| References_xml | – ident: IJAMC.2020100106-8 doi: 10.1007/978-3-540-31880-4_4 – ident: IJAMC.2020100106-22 doi: 10.1109/TEVC.2007.892759 – ident: IJAMC.2020100106-10 doi: 10.1109/TEVC.2005.861417 – ident: IJAMC.2020100106-0 doi: 10.1109/CEC.2001.934295 – start-page: 534 year: 2008 ident: IJAMC.2020100106-16 article-title: A decomposition-based multi-objective particle swarm optimization algorithm for continuous optimization problems. publication-title: Proceedings of IEEE International Conference on Granular Computing – ident: IJAMC.2020100106-18 doi: 10.1007/978-3-540-31880-4_35 – ident: IJAMC.2020100106-19 doi: 10.1109/MCI.2017.2742868 – ident: IJAMC.2020100106-24 doi: 10.1016/j.ins.2017.10.037 – ident: IJAMC.2020100106-26 doi: 10.1162/106365600568202 – ident: IJAMC.2020100106-13 doi: 10.1016/j.ejor.2015.06.071 – ident: IJAMC.2020100106-14 doi: 10.1145/2001576.2001587 – start-page: 2086 year: 2007 ident: IJAMC.2020100106-2 article-title: Improving hyper volume-based multi objective evolutionary algorithms by using objective reduction methods. publication-title: Proc. IEEE Congr. Evol. Comput., – ident: IJAMC.2020100106-3 doi: 10.1109/TCYB.2014.2322602 – ident: IJAMC.2020100106-23 doi: 10.1109/TEVC.2007.894202 – ident: IJAMC.2020100106-11 doi: 10.1109/ICNN.1995.488968 – ident: IJAMC.2020100106-25 doi: 10.1109/CEC.2006.1688406 – start-page: 95 year: 2001 ident: IJAMC.2020100106-28 article-title: SPEA2: Improving the strength Pareto evolutionary algorithm. publication-title: Proceedings of IEEE Conference on Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems – year: 2004 ident: IJAMC.2020100106-27 publication-title: Indicator-Based Selection in Multi objective Search – start-page: 825 year: 2002 ident: IJAMC.2020100106-7 article-title: Scalable multi objective optimization test problems. publication-title: Proceedings of IEEE Congress on Evolutionary Computation – ident: IJAMC.2020100106-21 doi: 10.1109/4235.585893 – ident: IJAMC.2020100106-1 doi: 10.1162/EVCO_a_00009 – ident: IJAMC.2020100106-5 doi: 10.1016/j.ins.2015.07.018 – ident: IJAMC.2020100106-15 doi: 10.1109/MCDM.2009.4938830 – ident: IJAMC.2020100106-20 doi: 10.1007/s40747-017-0057-5 – ident: IJAMC.2020100106-12 doi: 10.1016/j.ejor.2015.06.071 – ident: IJAMC.2020100106-6 doi: 10.1109/4235.996017 – ident: IJAMC.2020100106-17 doi: 10.1109/TEVC.2013.2281525 – ident: IJAMC.2020100106-9 doi: 10.1016/j.amc.2014.12.006 – ident: IJAMC.2020100106-4 doi: 10.1109/CEC.2002.1004388 |
| SSID | ssj0000547705 |
| Score | 2.149597 |
| Snippet | In this article, a new algorithm, namely the multi-objective competitive swarm optimizer (MOCSO), is introduced to handle multi-objective problems. The... |
| SourceID | proquest gale crossref igi |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 114 |
| SubjectTerms | Algorithms Analysis Archives & records Business metrics Competition Decomposition Efficiency Genetic algorithms Mathematical optimization Multiple objective analysis Objectives Optimization algorithms Optimization techniques Statistical tests |
| Title | A Novel Multi-Objective Competitive Swarm Optimization Algorithm |
| URI | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAMC.2020100106 https://www.proquest.com/docview/2931864365 |
| Volume | 11 |
| WOSCitedRecordID | wos000568375000006&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 | |
| journalDatabaseRights | – providerCode: PRVPQU databaseName: Computer Science Database customDbUrl: eissn: 1947-8291 dateEnd: 20221231 omitProxy: false ssIdentifier: ssj0000547705 issn: 1947-8283 databaseCode: K7- dateStart: 20100101 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1947-8291 dateEnd: 20221231 omitProxy: false ssIdentifier: ssj0000547705 issn: 1947-8283 databaseCode: BENPR dateStart: 20100101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB7RlgM98EYEShUkOHCwtk6c2D7RZdUKLtuKh9SbFb-WRfvqZlv-PmPHu0tV0QuXKFIcx5pxvnl6BuCdY8ah6KBE6EYQVjtGpC4dkd5alD5eNE7EZhN8OBQXF_I8OdzalFa5xsQI1HZugo-8h2KJChSfdfVxcUlC16gQXU0tNHZgjxYIwiEoy8nGx4LqCOcxixFNdR5OTJddpBKNCtH7grA2QAsxxIODZXRDMiV83hmPxrdQOoqe00f_u-jH8DApnXm_2yVP4J6bPYX9v0oRPoPjfj6cX7tJHk_kkjP9q0PCfBAV65hhlH_73Syn-RmizDQd38z7kxF-cPVz-hx-nJ58H3wmqbsCMaikrYgVDaNa-IbhHSo-1HBm8XfX3OlK6yNnaQiC-lAvhmlvpObUskraQtdSH-nyBezO5jP3EnLvCi2NpKywJWtELbymdUVRmSkN84XMoLemrDKp9HjogDFRaIIEXqjIC7XlRQYfNm8surIbd4x9H5ilUtdOvLTBr9GOmqu2VX1ehQJAshIZvEVuqvSPtrfmUQvrMzi-MQbpriLd1YbuKtL9X4uhNIOD9V7YzrPdCK_ufvwaHoTJunTBA9hdLa_cG7hvrlfjdnkIe59OhudfD-M2_wO6FP65 |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB61WyTKgTciUCBI9MAh2jpxEvuA6LK06qolraBIvblxbG8X7YvNthV_it_I2El2qSp664FLFCnOKJ6ZzDfjsWcA3mlaaIQOEjCZs4AmmgZcRjrgRilEH8NyzVyziTTL2MkJP1qB381ZGLutsrGJzlCrSWHXyNsIS4QhfCbxx-nPwHaNstnVpoVGpRb7-tclhmzlh95nlO9mGO7uHHf3grqrQFCgczIPFMspkczkFO8Q8EmRUoVqLlMtYym3tCI2-WdsnRQqTcFlShSNuQplwuWWjJDuKqzRiCZxC9Y-7WRHXxerOugApanbN0k4Te0Z7ajKjWIYw9o9NKRdjEltBtrGYlewsEaE1UF_cA0XHNjtPvjf2PQQ7tdutd-p_oNHsKLHj-HeX8UWn8B2x88mF3rouzPHwaH8Udl6v-tCB7eHyv92mc9G_iHa0VF9QNXvDPs4wfnZ6Cl8v5UpPIPWeDLWz8E3OpS84ISGKqI5S5iRJIkJumtRQU3IPWg3khRFXVzd9vgYCgyyrOyFk71Yyt6D94s3plVhkRvGblrlEHVfUryUduWm7OfnZSk6aWxLHPGYefAWtUfUVqi8RkdMlfFg-8oY5LtwfBcLvgvH9399DCEebDS6t6SzVLwXNz9-A3f3jr8ciINetv8S1i3hanPkBrTms3P9Cu4UF_NBOXtd_1w-nN62ov4BfctcUA |
| 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=A+Novel+Multi-Objective+Competitive+Swarm+Optimization+Algorithm&rft.jtitle=International+journal+of+applied+metaheuristic+computing&rft.au=Dey%2C+Nilanjan&rft.au=Kumar%2C+Ram&rft.au=Mohapatra%2C+Prabhujit&rft.au=Das%2C+Kedar&rft.date=2020-10-01&rft.pub=IGI+Global&rft.issn=1947-8283&rft.eissn=1947-8291&rft.volume=11&rft.issue=4&rft.spage=114&rft.epage=129&rft_id=info:doi/10.4018%2FIJAMC.2020100106 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1947-8283&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1947-8283&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1947-8283&client=summon |