supply chain management analyzing/modelling
Sajad Amirian; Maghsoud Amiri; Mohammad Taghi Taghavifard
Abstract
Purpose: In this research, a multi-product and multi-period closed-loop supply chain design problem with three objectives of profitability, social responsibility, and reliability under uncertain conditions has been considered.
Methodology: Triangular fuzzy numbers have been used for non-deterministic ...
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Purpose: In this research, a multi-product and multi-period closed-loop supply chain design problem with three objectives of profitability, social responsibility, and reliability under uncertain conditions has been considered.
Methodology: Triangular fuzzy numbers have been used for non-deterministic parameters and a robust probabilistic programming approach with Me scale has been used to deal with fuzzy constraints. The proposed approach eliminates the need for iterative consideration by decision-makers by providing unlimited choices from the optimism-pessimism spectrum. The mathematical model developed in this research is of mixed integer linear programming type, which is implemented in GAMS software to solve it and find Pareto optimal solutions.
Findings: The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the aluminum industry. The sensitivity analysis of the demand parameter showed that the proposed model achieved more economic profit, less social responsibility, and less reliability with increasing demand.
Originality/Value: The variability of the justified decision space in the Me criterion has helped to solve the supply chain network design problem more flexibly and closer to reality through the possibility of exchange between the objective function and the risk-taking level of the managers.
Mathematical Optimization Models
Elham Basiri
Abstract
Purpose: In this paper, the amount required to increase the reliability of the components of a coherent system is determined so that the cost of this increase is minimized and the reliability of the whole system is not less than the predetermined value.Methodology: In this research, after introducing ...
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Purpose: In this paper, the amount required to increase the reliability of the components of a coherent system is determined so that the cost of this increase is minimized and the reliability of the whole system is not less than the predetermined value.Methodology: In this research, after introducing the objective and constraint functions in the optimization problem, the Lagrange method is used and then the problem is solved by presenting an algorithm. In this article, several cost functions are considered, and then the results are presented in the general case for a coherent system and then for two special cases, series-parallel and parallel-series systems.Findings: In this article, two numerical examples are presented and solved. In the first example, a bridge structure is evaluated and in the second example, a series-parallel system is studied. In both examples, the required values are determined to increase the reliability of the system components.Originality/Value: This research, using a mathematical model and numerical calculations with the help of R software, examines the optimization problem for a coherent system.
supply chain management analyzing/modelling
Javad Mohammadghasemi; Seyyed Esmaeil Najafi; Mohammad Fallah; Mohammad Reza Nabatchian
Abstract
Purpose: This paper focuses on modeling a sustainable electricity industry supply chain network under uncertainty. The aim of presenting this supply chain network is to meet customer demands for solar panels to generate clean energy.Methodology: A mixed-integer linear programming model, including facility ...
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Purpose: This paper focuses on modeling a sustainable electricity industry supply chain network under uncertainty. The aim of presenting this supply chain network is to meet customer demands for solar panels to generate clean energy.Methodology: A mixed-integer linear programming model, including facility location, supplier selection, optimal flow allocation, and determination of the optimal price of solar panels in the network, is considered. The sustainability objectives of the model include maximizing the profit of the supply chain network, minimizing greenhouse gas emissions, and maximizing reliability. A robust optimization method is also considered to control uncertain parameters, and precise and innovative techniques are used to solve the model.Findings: The results of the model show that with an increase in network reliability, the current net value in the network decreases, and greenhouse gas emissions in the network increase. Additionally, the analysis of the results shows that with an increase in the network's uncertainty rate, the network's current net value and reliability decrease, and greenhouse gas emissions increase. Finally, the statistical test results also show that there was no significant difference between the averages of the number of practical solutions, the maximum spread, and the metric distance between the two algorithms, and only a significant difference exists between the solution times of the two algorithms. The results of the presented solution methods demonstrate their high efficiency in solving the sustainable electricity industry supply chain model.Originality/Value: In the proposed model, essential decisions such as supplier selection, establishment of production centers, optimal product flow allocation, and pricing of solar panels are made. On the other hand, further analyses of 15 numerical examples show the high efficiency of the MOALO and MOWOA algorithms compared to the epsilon-constraint method.