An improved Estimation of Distribution Algorithm for Solving Constrained Mixed-Integer Nonlinear Programming Problems
In a mixed-integer nonlinear programming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes. Evolutionary Algorithms (EAs) are usually vulnerable to being trapped in larger discontinuous feasible parts. In this work, an improved version of...
Uloženo v:
| Vydáno v: | 2022 IEEE Congress on Evolutionary Computation (CEC) s. 01 - 08 |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
18.07.2022
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | In a mixed-integer nonlinear programming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes. Evolutionary Algorithms (EAs) are usually vulnerable to being trapped in larger discontinuous feasible parts. In this work, an improved version of an Estimation of Distribution Algorithm (EDA) is developed, where two new op-erations are proposed. The first one establishes a link between the learning-based histogram model and the \varepsilon -constrained method. Here, the constraint violation level of the \varepsilon -constrained method is used to explore the smaller discontinuous parts and form a better statistical model. The second operation is the hybridization of the EDA with a mutation operator to generate offspring from both the global distribution information and the parent information. A benchmark is used to test the performance of the improved proposal. The results indicated that the proposed approach shows a better performance against other tested EAs. This new proposal solves to a great extent the influence of the larger discontinuous feasible parts, and improve the local refinement of the real variables. |
|---|---|
| AbstractList | In a mixed-integer nonlinear programming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes. Evolutionary Algorithms (EAs) are usually vulnerable to being trapped in larger discontinuous feasible parts. In this work, an improved version of an Estimation of Distribution Algorithm (EDA) is developed, where two new op-erations are proposed. The first one establishes a link between the learning-based histogram model and the \varepsilon -constrained method. Here, the constraint violation level of the \varepsilon -constrained method is used to explore the smaller discontinuous parts and form a better statistical model. The second operation is the hybridization of the EDA with a mutation operator to generate offspring from both the global distribution information and the parent information. A benchmark is used to test the performance of the improved proposal. The results indicated that the proposed approach shows a better performance against other tested EAs. This new proposal solves to a great extent the influence of the larger discontinuous feasible parts, and improve the local refinement of the real variables. |
| Author | Alfredo Portilla-Flores, Edgar Mezura-Montes, Efren Molina Perez, Daniel Vega-Alvarado, Eduardo |
| Author_xml | – sequence: 1 givenname: Daniel surname: Molina Perez fullname: Molina Perez, Daniel email: dmolinap1800@alumno.ipn.mx organization: Instituto Politécnico Nacional,CIDETEC,Ciudad de México,México – sequence: 2 givenname: Edgar surname: Alfredo Portilla-Flores fullname: Alfredo Portilla-Flores, Edgar email: aportilla@ipn.mx organization: Instituto Politécnico Nacional,UPIIT,Tlaxcala,México – sequence: 3 givenname: Efren surname: Mezura-Montes fullname: Mezura-Montes, Efren email: emezura@uv.mx organization: Artificial Intelligence Research Center University of Veracruz,Veracruz,México – sequence: 4 givenname: Eduardo surname: Vega-Alvarado fullname: Vega-Alvarado, Eduardo email: evega@ipn.mx organization: Instituto Politécnico Nacional,CIDETEC,Ciudad de México,México |
| BookMark | eNotkNtOwzAQRI0EElD6BQjJP5DgS3zJYxVKqVQuEvBcOfE6GCV25aQV_D0B-rQ7o7MjzV6i0xADIHRDSU4pKW-rZSUEkSJnhLG81Ipwrk_QvFSaSikKqYhW52g-DJ-EEKYZKbi8QPtFwL7fpXgAi5fD6Hsz-hhwdPjOD2Py9f5PL7o2Jj9-9NjFhF9jd_ChxVUME2N8mI4f_RfYbB1GaCHhpxi6yTYJv6TYJtP3v_y01x30wxU6c6YbYH6cM_R-v3yrHrLN82pdLTaZp5yPmbVNoaC0XFrhoGCMwdTG0YJp53jdCFYL56yjrHaslgVtlFC6IYZYo63TfIau_3M9AGx3aWqXvrfH5_AfGTBgCQ |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/CEC55065.2022.9870338 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume 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 |
| EISBN | 9781665467087 1665467088 |
| EndPage | 08 |
| ExternalDocumentID | 9870338 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IF 6IL 6IN AAWTH ABLEC ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK IEGSK OCL RIE RIL |
| ID | FETCH-LOGICAL-i133t-ddc47e9d36d5fe4222e781f1428ff3bc52b5ffdf12bf2b641c7578c0a0da8df83 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 5 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000859282000121&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 02:19:12 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i133t-ddc47e9d36d5fe4222e781f1428ff3bc52b5ffdf12bf2b641c7578c0a0da8df83 |
| PageCount | 8 |
| ParticipantIDs | ieee_primary_9870338 |
| PublicationCentury | 2000 |
| PublicationDate | 2022-July-18 |
| PublicationDateYYYYMMDD | 2022-07-18 |
| PublicationDate_xml | – month: 07 year: 2022 text: 2022-July-18 day: 18 |
| PublicationDecade | 2020 |
| PublicationTitle | 2022 IEEE Congress on Evolutionary Computation (CEC) |
| PublicationTitleAbbrev | CEC |
| PublicationYear | 2022 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0002820436 |
| Score | 1.8367639 |
| Snippet | In a mixed-integer nonlinear programming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes.... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 01 |
| SubjectTerms | Benchmark testing Estimation estimation of distribution algorithm evolution-ary algorithms Evolutionary computation Histograms integer restriction handling mixed integer non-linear programming Programming Proposals |
| Title | An improved Estimation of Distribution Algorithm for Solving Constrained Mixed-Integer Nonlinear Programming Problems |
| URI | https://ieeexplore.ieee.org/document/9870338 |
| WOSCitedRecordID | wos000859282000121&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/eLvHCXMwlV3PS8MwGA3b8OBJZRN_k4NHuzXpj7THMTc86BiosNtok--bha0d3Sb--eZry0Tw4q2UhkDCR773mvceY_fgCwESpKNVmjh-Kjxbc4iOjlAHSqHydCUUflbTaTSfx7MWezhoYQCgunwGfXqs_uWbQu-JKhtYfOxaSNVmbaXCWqt14FMsdCA39UakI9x4MBqPbPsdBhYEStlvxv4KUanOkMnJ_2Y_Zb0fMR6fHY6ZM9aCvMv2w5xnFR8Aho9tmdYKRF4gfyQr3CbFig9Xy8LC_481t80pfy1WxB9wSumssiHs4JfsC4xDxOASSj6tnTOSkqaki1tr-n5Wp85se-x9Mn4bPTlNgoKTWey5c4zRvoLYeKEJEIjtARUJJJc1RC_VgUwDRINCpijT0Bea7O21m7gmiQxG3jnr5EUOF4wLiyyMjhX6EPjKwjQTYmwrzNh-UEY6uWRdWrLFpjbJWDSrdfX362t2TLtCJKmIblhnV-7hlh3pz122Le-qnf0GIlaoNg |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1dS8MwFA1zCvqksonf5sFHuy3pR9rHMScTtzJwwt5Gm9zMwtZK14k_39y2TARffCulIZBwyT2nOecQcg8OY8CBW1LEkeXEzDY1p7UlfS1dIbSwZSkUHosw9OfzYNogDzstDACUl8-gg4_lv3yVyS1SZV2Dj3sGUu2RfUzOqtVaO0bFgAf0U69lOqwXdAfDgWnAPdfAQM479ehfMSrlKfJ0_L_5T0j7R45Hp7uD5pQ0IG2RbT-lSckIgKJDU6iVBpFmmj6iGW6dY0X7q2WWJ8X7mpr2lL5mK2QQKOZ0lukQZvAk-QJlITW4hJyGlXdGlOOUeHVrjd9Pq9yZTZu8PQ1ng5FVZyhYiUGfhaWUdAQEyvaUqwH5HhA-0-izprUdS5fHrtZKMx5rHnsOk2hwL3tRT0W-0r59RppplsI5ocxgCyUDoR1wHWGAmvJ0YGpMmY6Q-zK6IC1cssVHZZOxqFfr8u_Xd-RwNJuMF-Pn8OWKHOEOIWXK_GvSLPIt3JAD-Vkkm_y23OVvEIKrfw |
| 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=2022+IEEE+Congress+on+Evolutionary+Computation+%28CEC%29&rft.atitle=An+improved+Estimation+of+Distribution+Algorithm+for+Solving+Constrained+Mixed-Integer+Nonlinear+Programming+Problems&rft.au=Molina+Perez%2C+Daniel&rft.au=Alfredo+Portilla-Flores%2C+Edgar&rft.au=Mezura-Montes%2C+Efren&rft.au=Vega-Alvarado%2C+Eduardo&rft.date=2022-07-18&rft.pub=IEEE&rft.spage=01&rft.epage=08&rft_id=info:doi/10.1109%2FCEC55065.2022.9870338&rft.externalDocID=9870338 |