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Author: search.filters.author.Farbod Zahedi

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    Multi-objective sustainable closed-loop supply chain network design considering multiple products with different quality levels
    (MDPI, 2022-08-01)
    International laws and increasing consumer awareness have led to drastic changes in traditional supply chain network designs. Moreover, because of environmental and social require-ments, traditional supply chain networks have changed to sustainable supply chain networks. On the other hand, reverse logistics can be effective in terms of environmental and economic aspects, so the design of the supply chain network as a closed loop is necessary. In addition, customers have a demand for different products with different quality levels. Considering different types of customers with a variety of consumption trends can be a challenging issue, and is addressed in this study. The main contributions of this research are considering different quality levels for products as well as different tendencies of customers towards environmental issues. In this study, a sustainable closed-loop supply chain model is designed that seeks to balance economic, environmental, and social responsibilities. In this paper, costs and customer demands for different types of products at different quality levels are considered under uncertain conditions using a robust possibilistic programming method. The proposed multi-objective model is solved using the Augmented Epsilon Constraint (AEC) method that provides an efficient set of solutions for all decision-making levels. The results show that the robust possibilistic programming method is more effective in dealing with uncertainties than the possibilistic programming method.
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    Application of NSGA-II and Fuzzy TOPSIS to Time–Cost–Quality Trade-Off Resource Leveling for Scheduling an Agricultural Water Supply Project
    (Institute for Ionics, 2023-10-01)
    Access to sufficient and safe water particularly in vulnerable countries is one of the most important goals targeted by the United Nations for 2030. The agricultural water supply is crucial in arid areas such as Iran. In water supply projects, employers usually seek less duration and cost, and higher quality, however, contractors seek a reduction of fluctuations in project resources, especially human resources, and these goals may be in conflict with each other. Therefore, finding an optimal project schedule considering different project objectives is vital for managers to achieve stakeholders' satisfaction. In this study, the four main project objectives including time, cost, quality, and resource leveling as well as the activity dependencies and resource constraints are addressed through fuzzy optimization. The proposed model was first implemented on a small-sized project instance for validation; then, the model was solved by the Nondominated Sorting Genetic (NSGA-II) and Multi-objective Particle Swarm Optimization algorithms using the information of a real-world agricultural water supply project. The results of the first Pareto set for different alpha-cuts in relation to the fuzzy quality factor show a set of solutions and different alternatives for project implementation which leads to a number of execution modes each of which may result in achieving the project objectives. Finally, the most ideal solution with a duration of 178 days was selected using the fuzzy TOPSIS method. The findings demonstrate the validity of the proposed model concerning the needs of agricultural water supply organizations.