A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines
This research proposes a genetic regulatory network based sequencing method that minimizes multiple objectives including utility work costs, production rate variation costs and setup costs in mixed-model assembly lines. After constructing mathematical model of this multi-objective sequencing problem...
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| Format: | Article |
| Language: | English |
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AIMS Press
2019-02-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2019059?viewType=HTML |
| _version_ | 1819279268652253184 |
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| author | Youlong Lv Jie Zhang |
| author_facet | Youlong Lv Jie Zhang |
| author_sort | Youlong Lv |
| collection | DOAJ |
| description | This research proposes a genetic regulatory network based sequencing method that minimizes multiple objectives including utility work costs, production rate variation costs and setup costs in mixed-model assembly lines. After constructing mathematical model of this multi-objective sequencing problem, the proposed method generates a set of genes to represent the decision variables and develops a gene regulation equation to describe decision variable interactions composed of production constraints and some validated sequencing rules. Moreover, a gene expression procedure that determines each gene's expression state based on the gene regulation equation is designed. This enables the generation of a series of problem solutions by indicating decision variable values with related gene expression states, and realizes the minimization of weighted sum of multiple objectives by applying a regulatory parameter optimization mechanism in regulation equations. The proposed genetic regulatory network based sequencing method is validated through a series of comparative experiments, and the results demonstrate its effectiveness over other methods in terms of solution quality, especially for industrial instances collected from a diesel engine assembly line. |
| first_indexed | 2024-12-24T00:25:12Z |
| format | Article |
| id | doaj.art-94ed21b74af74417ab70771d4b6a2616 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-12-24T00:25:12Z |
| publishDate | 2019-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-94ed21b74af74417ab70771d4b6a26162022-12-21T17:24:27ZengAIMS PressMathematical Biosciences and Engineering1551-00182019-02-011631228124310.3934/mbe.2019059A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly linesYoulong Lv0Jie Zhang 1 College of Mechanical Engineering, Donghua University, 2999 North Renmin Road, Shanghai, China College of Mechanical Engineering, Donghua University, 2999 North Renmin Road, Shanghai, ChinaThis research proposes a genetic regulatory network based sequencing method that minimizes multiple objectives including utility work costs, production rate variation costs and setup costs in mixed-model assembly lines. After constructing mathematical model of this multi-objective sequencing problem, the proposed method generates a set of genes to represent the decision variables and develops a gene regulation equation to describe decision variable interactions composed of production constraints and some validated sequencing rules. Moreover, a gene expression procedure that determines each gene's expression state based on the gene regulation equation is designed. This enables the generation of a series of problem solutions by indicating decision variable values with related gene expression states, and realizes the minimization of weighted sum of multiple objectives by applying a regulatory parameter optimization mechanism in regulation equations. The proposed genetic regulatory network based sequencing method is validated through a series of comparative experiments, and the results demonstrate its effectiveness over other methods in terms of solution quality, especially for industrial instances collected from a diesel engine assembly line.https://www.aimspress.com/article/doi/10.3934/mbe.2019059?viewType=HTMLgenetic regulatory networkmultiple objectivessequencing problemmixed-model assembly linedifferential equationgene regulation |
| spellingShingle | Youlong Lv Jie Zhang A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines Mathematical Biosciences and Engineering genetic regulatory network multiple objectives sequencing problem mixed-model assembly line differential equation gene regulation |
| title | A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines |
| title_full | A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines |
| title_fullStr | A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines |
| title_full_unstemmed | A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines |
| title_short | A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines |
| title_sort | genetic regulatory network based method for multi objective sequencing problem in mixed model assembly lines |
| topic | genetic regulatory network multiple objectives sequencing problem mixed-model assembly line differential equation gene regulation |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2019059?viewType=HTML |
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