A DYNAMIC MULTI-OBJECTIVE APPROACH USING INTERVAL ANALYSIS AND GENETIC ALGORITHMS.
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| Title: | A DYNAMIC MULTI-OBJECTIVE APPROACH USING INTERVAL ANALYSIS AND GENETIC ALGORITHMS. |
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| Authors: | El Hraiech, Safa1 safa_el_hraiech@hotmail.fr, Chouaibi, Youssef2, Affi, Zouhaier1 |
| Source: | Transactions of FAMENA. 2026, Vol. 50 Issue 3, p17-30. 14p. |
| Subjects: | Interval analysis, Genetic algorithms, Parallel robots, Parameterization, Multi-objective optimization |
| Abstract: | This paper considers a multi-objective optimisation problem focusing on translational parallel manipulators. The proposed approach combines interval analysis with genetic algorithms to optimise the dynamic parameters of parallel manipulators. The objectives are to enhance the robot accuracy, while maximising the tolerance intervals of the parameters. This paper's contribution is to introduce an interval method to estimate the error bounds of a dynamic parallel manipulator within the desired workspace. A genetic algorithm is then applied to improve manipulator accuracy and reduce design costs. The resulting Pareto fronts illustrate the trade-off between each pair of objective functions. [ABSTRACT FROM AUTHOR] |
| Copyright of Transactions of FAMENA is the property of Faculty of Mechanical Engineering and Naval Architecture, University of Zegreb and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 197067061 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A DYNAMIC MULTI-OBJECTIVE APPROACH USING INTERVAL ANALYSIS AND GENETIC ALGORITHMS. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22El+Hraiech%2C+Safa%22">El Hraiech, Safa</searchLink><relatesTo>1</relatesTo><i> safa_el_hraiech@hotmail.fr</i><br /><searchLink fieldCode="AR" term="%22Chouaibi%2C+Youssef%22">Chouaibi, Youssef</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Affi%2C+Zouhaier%22">Affi, Zouhaier</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Transactions+of+FAMENA%22">Transactions of FAMENA</searchLink>. 2026, Vol. 50 Issue 3, p17-30. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Interval+analysis%22">Interval analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+robots%22">Parallel robots</searchLink><br /><searchLink fieldCode="DE" term="%22Parameterization%22">Parameterization</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper considers a multi-objective optimisation problem focusing on translational parallel manipulators. The proposed approach combines interval analysis with genetic algorithms to optimise the dynamic parameters of parallel manipulators. The objectives are to enhance the robot accuracy, while maximising the tolerance intervals of the parameters. This paper's contribution is to introduce an interval method to estimate the error bounds of a dynamic parallel manipulator within the desired workspace. A genetic algorithm is then applied to improve manipulator accuracy and reduce design costs. The resulting Pareto fronts illustrate the trade-off between each pair of objective functions. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Transactions of FAMENA is the property of Faculty of Mechanical Engineering and Naval Architecture, University of Zegreb and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.21278/TOF.503082825 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 17 Subjects: – SubjectFull: Interval analysis Type: general – SubjectFull: Genetic algorithms Type: general – SubjectFull: Parallel robots Type: general – SubjectFull: Parameterization Type: general – SubjectFull: Multi-objective optimization Type: general Titles: – TitleFull: A DYNAMIC MULTI-OBJECTIVE APPROACH USING INTERVAL ANALYSIS AND GENETIC ALGORITHMS. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: El Hraiech, Safa – PersonEntity: Name: NameFull: Chouaibi, Youssef – PersonEntity: Name: NameFull: Affi, Zouhaier IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 13331124 Numbering: – Type: volume Value: 50 – Type: issue Value: 3 Titles: – TitleFull: Transactions of FAMENA Type: main |
| ResultId | 1 |
