A particle swarm optimisation algorithm for multi-plant assembly sequence planning with integrated assembly sequence planning and plant assignment.
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| Title: | A particle swarm optimisation algorithm for multi-plant assembly sequence planning with integrated assembly sequence planning and plant assignment. |
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| Authors: | Tseng, Yuan-Jye1 (AUTHOR) ieyjt@saturn.yzu.edu.tw, Chen, Jian-Yu1 (AUTHOR), Huang, Feng-Yi1 (AUTHOR) |
| Source: | International Journal of Production Research. May2010, Vol. 48 Issue 10, p2765-2791. 27p. 4 Diagrams, 7 Charts, 2 Graphs. |
| Subjects: | Particle swarm optimization, Advanced planning & optimization, Assembly line methods, Operations research, Factories, Industrial costs |
| Abstract: | In a multi-plant collaborative manufacturing system, the manufacturing and assembly operations for producing a product can be distributed at different plants at different locations. In this research, a multi-plant assembly sequence planning model is presented by integrating assembly sequence planning and plant assignment and is solved using a particle swarm optimisation (PSO) algorithm. In assembly sequence planning, the components and assembly operations are sequenced according to the operational constraints and precedence constraints to achieve assembly cost objectives. In plant assignment, the components and assembly operations are assigned to the suitable plants under the constraints of plant capabilities to achieve multi-plant cost objectives. A new PSO encoding scheme is presented in which a particle is defined by a position matrix defined by the numbers of components and plants. The PSO algorithm simultaneously performs assembly sequence planning of components and assignment of plants with an objective of minimising the total of assembly operational costs and multi-plant costs. The main contribution lies in the new multi-plant assembly sequence planning model and the new PSO solution scheme. An example product is tested and illustrated. The test results show that the presented method is feasible and efficient for solving the multi-plant assembly sequence planning problem. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 49143969 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A particle swarm optimisation algorithm for multi-plant assembly sequence planning with integrated assembly sequence planning and plant assignment. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tseng%2C+Yuan-Jye%22">Tseng, Yuan-Jye</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ieyjt@saturn.yzu.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Jian-Yu%22">Chen, Jian-Yu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Feng-Yi%22">Huang, Feng-Yi</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. May2010, Vol. 48 Issue 10, p2765-2791. 27p. 4 Diagrams, 7 Charts, 2 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Advanced+planning+%26+optimization%22">Advanced planning & optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Assembly+line+methods%22">Assembly line methods</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink><br /><searchLink fieldCode="DE" term="%22Factories%22">Factories</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+costs%22">Industrial costs</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In a multi-plant collaborative manufacturing system, the manufacturing and assembly operations for producing a product can be distributed at different plants at different locations. In this research, a multi-plant assembly sequence planning model is presented by integrating assembly sequence planning and plant assignment and is solved using a particle swarm optimisation (PSO) algorithm. In assembly sequence planning, the components and assembly operations are sequenced according to the operational constraints and precedence constraints to achieve assembly cost objectives. In plant assignment, the components and assembly operations are assigned to the suitable plants under the constraints of plant capabilities to achieve multi-plant cost objectives. A new PSO encoding scheme is presented in which a particle is defined by a position matrix defined by the numbers of components and plants. The PSO algorithm simultaneously performs assembly sequence planning of components and assignment of plants with an objective of minimising the total of assembly operational costs and multi-plant costs. The main contribution lies in the new multi-plant assembly sequence planning model and the new PSO solution scheme. An example product is tested and illustrated. The test results show that the presented method is feasible and efficient for solving the multi-plant assembly sequence planning problem. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd 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: 10.1080/00207540902791835 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 2765 Subjects: – SubjectFull: Particle swarm optimization Type: general – SubjectFull: Advanced planning & optimization Type: general – SubjectFull: Assembly line methods Type: general – SubjectFull: Operations research Type: general – SubjectFull: Factories Type: general – SubjectFull: Industrial costs Type: general Titles: – TitleFull: A particle swarm optimisation algorithm for multi-plant assembly sequence planning with integrated assembly sequence planning and plant assignment. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tseng, Yuan-Jye – PersonEntity: Name: NameFull: Chen, Jian-Yu – PersonEntity: Name: NameFull: Huang, Feng-Yi IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2010 Type: published Y: 2010 Identifiers: – Type: issn-print Value: 00207543 Numbering: – Type: volume Value: 48 – Type: issue Value: 10 Titles: – TitleFull: International Journal of Production Research Type: main |
| ResultId | 1 |
