Multiverse Optimization Algorithm for Stochastic Biobjective Disassembly Sequence Planning Subject to Operation Failures.
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| Title: | Multiverse Optimization Algorithm for Stochastic Biobjective Disassembly Sequence Planning Subject to Operation Failures. |
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| Authors: | Fu, Yaping1 (AUTHOR) fuyaping0432@163.com, Zhou, MengChu2 (AUTHOR) zhou@njit.edu, Guo, Xiwang2 (AUTHOR) x.w.guo@163.com, Qi, Liang3 (AUTHOR) qiliangsdkd@163.com, Sedraoui, Khaled4 (AUTHOR) sedraoui@yahoo.com |
| Source: | IEEE Transactions on Systems, Man & Cybernetics. Systems. Jan2022, Vol. 52 Issue 1, p1041-1051. 11p. |
| Subjects: | Mathematical optimization, Remanufacturing, Energy consumption, Waste recycling, Economic indicators, Markov processes |
| Abstract: | Disassembly is an essential step in a remanufacturing process via which valuable parts and material of end-of-life (EOL) products can be well reused and resource waste is reduced. Disassembly sequence planning focuses on finding the best disassembly sequence for a given EOL product by considering economic and environmental performance. In a practical disassembly process, one may face a disassembly operation failure risk due to the difficulty of knowing EOL products’ exact information in advance. Despite its importance in impacting disassembly outcomes, the existing work fails to consider it comprehensively. This work proposes a stochastic biobjective DSP problem with the objectives of maximizing disassembly profit and minimizing energy consumption by doing so. A chance-constrained programming model is established, where a chance constraint ensures a fixed confidence level of disassembly failure. To solve it efficiently, a multiobjective multiverse optimization algorithm with stochastic simulation is proposed. Experiments are carried out on four products. Results demonstrate that it outperforms some state-of-the-art algorithms in terms of solution performance. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Transactions on Systems, Man & Cybernetics. Systems is the property of IEEE 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 | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 154801017 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multiverse Optimization Algorithm for Stochastic Biobjective Disassembly Sequence Planning Subject to Operation Failures. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Fu%2C+Yaping%22">Fu, Yaping</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> fuyaping0432@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+MengChu%22">Zhou, MengChu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> zhou@njit.edu</i><br /><searchLink fieldCode="AR" term="%22Guo%2C+Xiwang%22">Guo, Xiwang</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> x.w.guo@163.com</i><br /><searchLink fieldCode="AR" term="%22Qi%2C+Liang%22">Qi, Liang</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> qiliangsdkd@163.com</i><br /><searchLink fieldCode="AR" term="%22Sedraoui%2C+Khaled%22">Sedraoui, Khaled</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> sedraoui@yahoo.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Systems%2C+Man+%26+Cybernetics%2E+Systems%22">IEEE Transactions on Systems, Man & Cybernetics. Systems</searchLink>. Jan2022, Vol. 52 Issue 1, p1041-1051. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Remanufacturing%22">Remanufacturing</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Waste+recycling%22">Waste recycling</searchLink><br /><searchLink fieldCode="DE" term="%22Economic+indicators%22">Economic indicators</searchLink><br /><searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Disassembly is an essential step in a remanufacturing process via which valuable parts and material of end-of-life (EOL) products can be well reused and resource waste is reduced. Disassembly sequence planning focuses on finding the best disassembly sequence for a given EOL product by considering economic and environmental performance. In a practical disassembly process, one may face a disassembly operation failure risk due to the difficulty of knowing EOL products’ exact information in advance. Despite its importance in impacting disassembly outcomes, the existing work fails to consider it comprehensively. This work proposes a stochastic biobjective DSP problem with the objectives of maximizing disassembly profit and minimizing energy consumption by doing so. A chance-constrained programming model is established, where a chance constraint ensures a fixed confidence level of disassembly failure. To solve it efficiently, a multiobjective multiverse optimization algorithm with stochastic simulation is proposed. Experiments are carried out on four products. Results demonstrate that it outperforms some state-of-the-art algorithms in terms of solution performance. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Systems, Man & Cybernetics. Systems is the property of IEEE 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: 10.1109/TSMC.2021.3049323 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1041 Subjects: – SubjectFull: Mathematical optimization Type: general – SubjectFull: Remanufacturing Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Waste recycling Type: general – SubjectFull: Economic indicators Type: general – SubjectFull: Markov processes Type: general Titles: – TitleFull: Multiverse Optimization Algorithm for Stochastic Biobjective Disassembly Sequence Planning Subject to Operation Failures. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fu, Yaping – PersonEntity: Name: NameFull: Zhou, MengChu – PersonEntity: Name: NameFull: Guo, Xiwang – PersonEntity: Name: NameFull: Qi, Liang – PersonEntity: Name: NameFull: Sedraoui, Khaled IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Jan2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 21682216 Numbering: – Type: volume Value: 52 – Type: issue Value: 1 Titles: – TitleFull: IEEE Transactions on Systems, Man & Cybernetics. Systems Type: main |
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