Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers
The application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leadin...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Sustainable Futures |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666188824001771 |
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| author | Hamed Ghamari Hamidreza Abbasianjahromi Seyed Mohammad Mirhosseini |
| author_facet | Hamed Ghamari Hamidreza Abbasianjahromi Seyed Mohammad Mirhosseini |
| author_sort | Hamed Ghamari |
| collection | DOAJ |
| description | The application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leading to more effective project execution. Despite its importance, limited research has focused on designing sustainable supply chains for construction materials under uncertain conditions. This study aims to bridge this gap by introducing a robust optimization framework that incorporates sustainable development criteria, specifically the minimization of harmful environmental effects and the reduction of worker unemployment. Additionally, the research introduces an innovative concept of horizontal transfers between downstream members, which not only reduces supply deficiencies but also indirectly increases profitability for these members. This article is a part of a Doctoral dissertation. It follows a two-step approach. First, suppliers of construction materials are ranked based on sustainable development criteria using a multi-criteria decision-making method. The best-ranked supplier is then integrated into a mathematical model for optimizing the supply chain design. Given the NP-hard nature of the problem, the CPLEX 12.1 solver with the epsilon constraint method is used to solve small-scale models. For larger-scale problems, three meta-heuristic algorithms are developed: multi-objective ant-lion, multi-objective gray wolf, and multi-objective dragonfly. The results show that while both the ant-lion and gray wolf algorithms deliver comparable average performance, the gray wolf algorithm excels in terms of solution time, making it more effective for real-time problem-solving. This makes the gray wolf algorithm the most efficient choice for addressing large-scale, multi-objective supply chain challenges. This research introduces a novel framework for designing sustainable construction supply chains under uncertain conditions. By focusing on criteria such as minimizing harmful environmental effects and reducing worker unemployment, this study addresses key aspects of sustainable development. Additionally, the innovative horizontal transfer mechanism and the insights into algorithmic performance provide valuable contributions to the field, especially for real-world applications in the construction industry. |
| format | Article |
| id | doaj-art-bd466f4b4a5f4aeb98730b8240bcca7e |
| institution | OA Journals |
| issn | 2666-1888 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Sustainable Futures |
| spelling | doaj-art-bd466f4b4a5f4aeb98730b8240bcca7e2025-08-20T01:57:52ZengElsevierSustainable Futures2666-18882024-12-01810032810.1016/j.sftr.2024.100328Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfersHamed Ghamari0Hamidreza Abbasianjahromi1Seyed Mohammad Mirhosseini2Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, IranDepartment of Civil Engineering, K. N. Toosi University of Technology, Iran; Corresponding author.Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, IranThe application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leading to more effective project execution. Despite its importance, limited research has focused on designing sustainable supply chains for construction materials under uncertain conditions. This study aims to bridge this gap by introducing a robust optimization framework that incorporates sustainable development criteria, specifically the minimization of harmful environmental effects and the reduction of worker unemployment. Additionally, the research introduces an innovative concept of horizontal transfers between downstream members, which not only reduces supply deficiencies but also indirectly increases profitability for these members. This article is a part of a Doctoral dissertation. It follows a two-step approach. First, suppliers of construction materials are ranked based on sustainable development criteria using a multi-criteria decision-making method. The best-ranked supplier is then integrated into a mathematical model for optimizing the supply chain design. Given the NP-hard nature of the problem, the CPLEX 12.1 solver with the epsilon constraint method is used to solve small-scale models. For larger-scale problems, three meta-heuristic algorithms are developed: multi-objective ant-lion, multi-objective gray wolf, and multi-objective dragonfly. The results show that while both the ant-lion and gray wolf algorithms deliver comparable average performance, the gray wolf algorithm excels in terms of solution time, making it more effective for real-time problem-solving. This makes the gray wolf algorithm the most efficient choice for addressing large-scale, multi-objective supply chain challenges. This research introduces a novel framework for designing sustainable construction supply chains under uncertain conditions. By focusing on criteria such as minimizing harmful environmental effects and reducing worker unemployment, this study addresses key aspects of sustainable development. Additionally, the innovative horizontal transfer mechanism and the insights into algorithmic performance provide valuable contributions to the field, especially for real-world applications in the construction industry.http://www.sciencedirect.com/science/article/pii/S2666188824001771Sustainable supply chain managementSustainable construction materials supply chainMulti-objective gray wolfMulti-objective Ant-lionMulti-objective dragonfly |
| spellingShingle | Hamed Ghamari Hamidreza Abbasianjahromi Seyed Mohammad Mirhosseini Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers Sustainable Futures Sustainable supply chain management Sustainable construction materials supply chain Multi-objective gray wolf Multi-objective Ant-lion Multi-objective dragonfly |
| title | Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers |
| title_full | Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers |
| title_fullStr | Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers |
| title_full_unstemmed | Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers |
| title_short | Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers |
| title_sort | providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers |
| topic | Sustainable supply chain management Sustainable construction materials supply chain Multi-objective gray wolf Multi-objective Ant-lion Multi-objective dragonfly |
| url | http://www.sciencedirect.com/science/article/pii/S2666188824001771 |
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