Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain
A two-stage cold supply chain manages the transportation, storage, and distribution of temperature-sensitive products like frozen food, fresh/green products, and pharmaceuticals, which makes it costly. It consists of three key elements: a supplier, a warehouse, and multiple customers. Procurement pl...
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MDPI AG
2025-03-01
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| author | Aslı Acerce Berrin Denizhan |
| author_facet | Aslı Acerce Berrin Denizhan |
| author_sort | Aslı Acerce |
| collection | DOAJ |
| description | A two-stage cold supply chain manages the transportation, storage, and distribution of temperature-sensitive products like frozen food, fresh/green products, and pharmaceuticals, which makes it costly. It consists of three key elements: a supplier, a warehouse, and multiple customers. Procurement planning can be conducted for various products, and this study assumes the transport of a fresh/green product with gradually decreasing quality due to its perishable nature. In a two-stage cold supply chain, multiple objective functions can be defined, including cost minimization, product quality optimization, and transportation/storage condition optimization. We developed a mathematical model to optimize these objectives, incorporating two specific functions, cost minimization and product age reduction, to ensure efficient supply chain performance. Traditional solution methods often struggle with multi-objective mathematical models due to their complexity. Therefore, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a Genetic Algorithm-based approach, was applied to solve the model efficiently. NSGA-II optimized planning for a 7-day period under specific demand conditions, ensuring better resource allocation. The results showed that NSGA-II was better than traditional methods at making decisions and routing efficiently in the two-stage cold supply chain. This led to much better outcomes, with lower costs, less waste, and better product quality throughout the process. |
| format | Article |
| id | doaj-art-10f262b03cfb469ba6da4e35df8fa8f9 |
| institution | DOAJ |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| series | Systems |
| spelling | doaj-art-10f262b03cfb469ba6da4e35df8fa8f92025-08-20T02:43:09ZengMDPI AGSystems2079-89542025-03-0113320610.3390/systems13030206Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply ChainAslı Acerce0Berrin Denizhan1Department of Industrial Engineering, Engineering Faculty, Sakarya University, 54050 Sakarya, TurkeyDepartment of Industrial Engineering, Engineering Faculty, Sakarya University, 54050 Sakarya, TurkeyA two-stage cold supply chain manages the transportation, storage, and distribution of temperature-sensitive products like frozen food, fresh/green products, and pharmaceuticals, which makes it costly. It consists of three key elements: a supplier, a warehouse, and multiple customers. Procurement planning can be conducted for various products, and this study assumes the transport of a fresh/green product with gradually decreasing quality due to its perishable nature. In a two-stage cold supply chain, multiple objective functions can be defined, including cost minimization, product quality optimization, and transportation/storage condition optimization. We developed a mathematical model to optimize these objectives, incorporating two specific functions, cost minimization and product age reduction, to ensure efficient supply chain performance. Traditional solution methods often struggle with multi-objective mathematical models due to their complexity. Therefore, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a Genetic Algorithm-based approach, was applied to solve the model efficiently. NSGA-II optimized planning for a 7-day period under specific demand conditions, ensuring better resource allocation. The results showed that NSGA-II was better than traditional methods at making decisions and routing efficiently in the two-stage cold supply chain. This led to much better outcomes, with lower costs, less waste, and better product quality throughout the process.https://www.mdpi.com/2079-8954/13/3/206two-echelon inventory systemcold supply chainmulti-objective functionmeta-heuristic algorithmNSGA-II |
| spellingShingle | Aslı Acerce Berrin Denizhan Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain Systems two-echelon inventory system cold supply chain multi-objective function meta-heuristic algorithm NSGA-II |
| title | Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain |
| title_full | Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain |
| title_fullStr | Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain |
| title_full_unstemmed | Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain |
| title_short | Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain |
| title_sort | application of the non dominated sorting genetic algorithm ii nsga ii in a two echelon cold supply chain |
| topic | two-echelon inventory system cold supply chain multi-objective function meta-heuristic algorithm NSGA-II |
| url | https://www.mdpi.com/2079-8954/13/3/206 |
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