Supply chain management
Mohammad Reza Razdan; Saeed Aghasi; Sayyed Mohammad Reza Davoodi
Abstract
Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, ...
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Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, qualitativeness and incomplete and sometimes contradictory information. Therefore, their ranking needs the techniques that can model the mentioned issues. neutrosophic logic makes it possible to model propositions with uncertainty, incomplete information, ambiguity, qualitativeness, and even inconsistency. Accordingly, the approach of the present study is to use a combined method of neutrosophic hierarchical analysis and TOPSIS for ranking the risk. Core of this paper is proposed a hybrid decision making method for identification and ranking of supply chain management by a Neutrosophic analytical hierarchy process and TOPSIS approach. The case study is Mobarakeh Steel Company of Isfahan and three criteria including resilience, agility and robustness are considered as major strategies to deal with risk and seventeen risk-related issues are ranked as options. The results show that government constraints, economic and environmental risks, inventory shortages, technology risk, forecast risk and financial (cash) problems are the most important risks threatening the supply chain. Therefore, we believe that the proposed framework provides managers with valuable knowledge for decision making.
Supply chain management
Mona Beiranvand; Sayyed Mohammad Reza Davoodi
Abstract
Today, one of the topics in supply chain management is "multiple sales channels" and "pricing". In this research, a food producer (west Sahar Dasht Company) has been selected, and several retailers and wholesalers have been considered as the company's customers. This research dynamically solves the model ...
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Today, one of the topics in supply chain management is "multiple sales channels" and "pricing". In this research, a food producer (west Sahar Dasht Company) has been selected, and several retailers and wholesalers have been considered as the company's customers. This research dynamically solves the model through the game theory method. To obtain the equilibrium point and Stockelberg, the lower level optimal values (retailers and suppliers) are calculated based on the higher-level values (manufacturer), which turns the multi-level model into a single-level model to calculate the higher level optimal values. By presenting a case study and analyzing the sensitivity of the parameters, it was shown that some changes in the parameters have a significant effect on the problem variables, and its equilibrium model is better. Because game theory is proposed to solve problems on a small scale, and because the present problem is so complex, genetic algorithm meta-heuristic and particle aggregation optimization have been used to solve medium and large problems. To validate their results, they are compared with the results obtained from the mathematical model. Finally, comparing the performance of the two meta-heuristic algorithms through statistical analysis has shown that the particle aggregation optimization algorithm performs better than the genetic algorithm.
Supply chain management
Somayeh Sazegari; Sayyed Mohammad Reza Davoodi; Alireza Goli
Abstract
Today, most supply chains are moving towards green business with a greater focus on environmental protection as a competitive advantage. Among them, the design of a three-stage green supply chain with optimal allocation, a multiple supply chain that includes supplier (first stage), manufacturer (second ...
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Today, most supply chains are moving towards green business with a greater focus on environmental protection as a competitive advantage. Among them, the design of a three-stage green supply chain with optimal allocation, a multiple supply chain that includes supplier (first stage), manufacturer (second stage) and distributor (third stage), based on maximum efficiency and considering the internal processes and products between these three levels, can be of special importance; because, it will increase the economic and environmental performance of the supply chain. One of the methods used to evaluate efficiency in Green Supply Chain Management (GSCM) is Data Envelopment Analysis (DEA). Therefore, performance evaluation is vital for companies to improve the effectiveness and efficiency of the supply chain. In this study, using the three-stage approach of DEA, the data collected in 2020 from 9 Selected home appliance companies have been analyzed. The results show that company 1 has the best efficiency and the greenest supply chain and company 7 has the worst value of efficiency, which makes it necessary to pay more attention to low performance companies. In order to show the capability of the proposed model, the developed model was compared with its equivalent base model, and companies 1 and 2 were identified as inefficient in the proposed model, but identified as efficient in the base model. Given that the efficiency score in the proposed model is always lower than the base model, so the accuracy of the developed model can be concluded.
