Volume 35, Issue 1 (IJIEPR 2024)                   IJIEPR 2024, 35(1): 1-16 | Back to browse issues page


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Dargahi Darabad S, Izadbakhsh M, Ghannadpour S F, Noori S, Mahdavi mazdeh M. A new bi-objective green construction model for multi project supply chain management under uncertainty. IJIEPR 2024; 35 (1) :1-16
URL: http://ijiepr.iust.ac.ir/article-1-1813-en.html
1- School of industrial Engineering, Iran University of Science and Technology
2- Assistant professor, School of industrial Engineering, Iran University of Science and Technology , ghannadpour@iust.ac.ir
Abstract:   (823 Views)
The construction supply chain is presently the focus of considerable interest among numerous project-related businesses. Strong project management is essential for the effective completion of a project, since restricted budgets and time constraints are considered for each project. The research uses multi-objective linear programming to create a mathematical model of the building supply chain. The primary aims of the present investigation are to limit the expenses associated with logistics and to diminish the release of greenhouse gases caused by transportation. Given the reality of managing several projects concurrently, the model provided comprises a network of projects. Following the completion of each project, an inspection is arranged to assess its level of success. Estimating the costs of a project relies on several variables. In reality, there are always uncertainties highlighted in several studies about the uncertainty of cost and time parameters. This research incorporates many characteristics concurrently to simulate real-world settings and address the issue of uncertainty. The expression of uncertainty for all costs, activity length, inspection, supplier capacity, and resource demand are represented by triangular fuzzy numbers. Ultimately, the precision of the model's performance has been verified using a numerical illustration.
Full-Text [PDF 688 kb]   (551 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2023/05/24 | Accepted: 2024/01/14 | Published: 2024/03/11

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