Optimization of the supply chain network planning problem using an improved genetic algorithm
The planning problem of supply chain network is highly related to logistics cost and product quality. In this paper, for the optimization of supply chain network planning problem, an agricultural product supply chain network under the direct docking model between farmers and supermarkets was taken a...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | International Journal for Simulation and Multidisciplinary Design Optimization |
| Subjects: | |
| Online Access: | https://www.ijsmdo.org/articles/smdo/full_html/2023/01/smdo230030/smdo230030.html |
| _version_ | 1797673451835621376 |
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| author | Zhao Liang Xie Jing |
| author_facet | Zhao Liang Xie Jing |
| author_sort | Zhao Liang |
| collection | DOAJ |
| description | The planning problem of supply chain network is highly related to logistics cost and product quality. In this paper, for the optimization of supply chain network planning problem, an agricultural product supply chain network under the direct docking model between farmers and supermarkets was taken as an example to establish an agricultural product supply chain network planning model with the lowest cost as the objective. Then, an improved genetic algorithm (GA) was designed to solve the model. The analysis of the arithmetic example showed that compared with the traditional GA, the total cost obtained by the improved GA was lower, at 39,004.48 $, which was 6.5% less than that of the traditional GA; the solution result of the improved GA was also superior to that of other heuristic algorithms, such as particle swarm optimization and ant colony optimization. The experimental results demonstrate the optimization effectiveness of the improved GA for the supply chain network planning problem, and it can be applied in practice. |
| first_indexed | 2024-03-11T21:44:37Z |
| format | Article |
| id | doaj.art-744329740f5a4180abbb6d2fafe7ac0f |
| institution | Directory Open Access Journal |
| issn | 1779-6288 |
| language | English |
| last_indexed | 2024-03-11T21:44:37Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | International Journal for Simulation and Multidisciplinary Design Optimization |
| spelling | doaj.art-744329740f5a4180abbb6d2fafe7ac0f2023-09-26T10:13:34ZengEDP SciencesInternational Journal for Simulation and Multidisciplinary Design Optimization1779-62882023-01-0114910.1051/smdo/2023014smdo230030Optimization of the supply chain network planning problem using an improved genetic algorithmZhao Liang0Xie Jing1Department of Railway Engineering, Zhengzhou Railway Vocational and Technical CollegeInnovation and Entrepreneurship Institute, Zhengzhou Railway Vocational and Technical CollegeThe planning problem of supply chain network is highly related to logistics cost and product quality. In this paper, for the optimization of supply chain network planning problem, an agricultural product supply chain network under the direct docking model between farmers and supermarkets was taken as an example to establish an agricultural product supply chain network planning model with the lowest cost as the objective. Then, an improved genetic algorithm (GA) was designed to solve the model. The analysis of the arithmetic example showed that compared with the traditional GA, the total cost obtained by the improved GA was lower, at 39,004.48 $, which was 6.5% less than that of the traditional GA; the solution result of the improved GA was also superior to that of other heuristic algorithms, such as particle swarm optimization and ant colony optimization. The experimental results demonstrate the optimization effectiveness of the improved GA for the supply chain network planning problem, and it can be applied in practice.https://www.ijsmdo.org/articles/smdo/full_html/2023/01/smdo230030/smdo230030.htmlgenetic algorithmsupply chain networkplanningagricultural productcost |
| spellingShingle | Zhao Liang Xie Jing Optimization of the supply chain network planning problem using an improved genetic algorithm International Journal for Simulation and Multidisciplinary Design Optimization genetic algorithm supply chain network planning agricultural product cost |
| title | Optimization of the supply chain network planning problem using an improved genetic algorithm |
| title_full | Optimization of the supply chain network planning problem using an improved genetic algorithm |
| title_fullStr | Optimization of the supply chain network planning problem using an improved genetic algorithm |
| title_full_unstemmed | Optimization of the supply chain network planning problem using an improved genetic algorithm |
| title_short | Optimization of the supply chain network planning problem using an improved genetic algorithm |
| title_sort | optimization of the supply chain network planning problem using an improved genetic algorithm |
| topic | genetic algorithm supply chain network planning agricultural product cost |
| url | https://www.ijsmdo.org/articles/smdo/full_html/2023/01/smdo230030/smdo230030.html |
| work_keys_str_mv | AT zhaoliang optimizationofthesupplychainnetworkplanningproblemusinganimprovedgeneticalgorithm AT xiejing optimizationofthesupplychainnetworkplanningproblemusinganimprovedgeneticalgorithm |