Integrating IVFRN-BWM and Goal Programming to Allocate the Order Quantity Considering Discount for Green Supplier

Лю, Пэйдэ; Hendalianpour, Ayad; Fakhrabadi, Mahnaz; Feylizadeh, Mohammad Reza

doi:10.1007/s40815-021-01181-z

Cited by 22 publications

(9 citation statements)

References 69 publications

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“…The BWM has also been applied by scholars to solve decision problems in supply chain management. Liu, et al [34] used a modified BWM to prioritize and weigh suppliers. Haseli, et al [35] developed a new method G-BWM based on BWM group decision problem, and applied it to green supplier selection and supplier development.…”

Section: Best-worst Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Energy Supply Chain Risk Evaluation based on a Two-Stage Decision Making Approach

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

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Energy has always been an important issue related to people's livelihood and economy. With the energy crisis continues to escalate, the problems exposed in the energy supply chain are becoming increasingly severe. Due to the uncertainty of the external environment and internal structure, the energy supply chain is vulnerable to various risks. This article takes three representative energy companies in China as examples and adopts a two-stage method to evaluate the risks of the energy supply chain. The first stage uses the best-worst method (BWM) to determine the weight of each risk factor, and the second stage uses the linguistic value soft set to evaluate the risk performance of energy companies, and finally obtains the ranking results of the energy supply chain of each company. The results show that none of the three companies have outstanding performance in environmental-related risks, and energy companies should pay more attention to the control of environmental risks. This research supplements the related research on energy supply chain risk in theory, and has guiding significance for practitioners in related industries.

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Section: Best-worst Methodsmentioning

confidence: 99%

“…1 11, 13, 14, 16, 17, 18, 21, 22, 23, 24, 31, 32, 33, 34, 41, 42 12,13,15,16,17,21,22,23,24,31,32,33,34,41,42, 43 11,12,13,14,15,16,17,18,21,22,23,24,31,32,34,42, 43…”

Section: Empirical Analysismentioning

confidence: 99%

Energy Supply Chain Risk Evaluation based on a Two-Stage Decision Making Approach

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

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“…Another study by P. Liu et al [41] presented a multiobjective linear programming model that prioritized and weighed suppliers for effective supply chain management (SCM). The model used fuzzy variables to determine the number of suppliers and order quantities of raw materials and solved constraints using the goal programming method.…”

Section: Literature Reviewmentioning

confidence: 99%

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

Zhou

Štilić²,

Stević

et al. 2023

Sustainability

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Green supplier selection is always one of the most important challenges in all of supply chain management, especially for production companies. The purpose is to have reliable suppliers which can fulfill all requests and be flexible in any supply chain stage. The aim of this paper is to create an adequate and strong MCDM (multicriteria decision making) model for the evaluation and selection of suppliers in a real environment. The main contribution of this study is proposing a novel fuzzy–rough MCDM model containing extension stepwise weight assessment ratio analysis (SWARA) and additive ratio assessment (ARAS) methods with fuzzy–rough numbers (FRN). The integrated FRN SWARA–FRN ARAS model was implemented in a case study of eco-friendly material production. The FRN SWARA method was used to calculate the weights of 10 green criteria, while using FRN ARAS, 6 suppliers were evaluated. The results of the applied model show that supplier S3 received the highest ranking, followed by supplier S2, while supplier S5 performed the poorest. In order to verify the strengths of the developed fuzzy–rough approach, we created a comparative analysis, sensitivity analysis, and dynamic matrix, which confirm the robustness of our model.

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“…Liu et al [77] put forward a linear MODM model to help manage supply chains through the efficient selection of suppliers and allocation of orders. The study introduced a modified BWM method to assess and prioritize suppliers.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable Supplier Selection and Order Allocation Using an Integrated ROG-Based Type-2 Fuzzy Decision-Making Approach

Ghorabaee

2023

Mathematics

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The sustainable Supplier Evaluation and Selection and Order Allocation (SSOA) problem has received significant attention in supply chain management due to its potential to enhance a company’s performance, improve customer satisfaction, and reduce costs. In this study, an integrated methodology is proposed to address the SSOA problem. The methodology combines multiple techniques to handle the uncertainties associated with supplier evaluation, including a new ranking method based on the concept of Radius of Gyration (ROG) for interval type-2 fuzzy sets. The methodology also incorporates both subjective weights obtained using the Simple Multi-Attribute Rating Technique (SMART) and expert preferences, and objective weights calculated using the Method based on the Removal Effects of Criteria (MEREC) method to determine the weights of evaluation criteria. Some criteria for sustainable development are used to evaluate supplier performance, resulting in type-2 fuzzy sets, which are evaluated using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The ROG-based ranking method is employed to calculate the relative scores of suppliers. Finally, a multi-objective decision-making (MODM) mathematical model is presented to identify suitable suppliers and allocate their order quantities. The methodology is demonstrated in a sustainable SSOA problem and is shown to be efficient and effective, as the ROG-based ranking method allows for more accurate supplier performance evaluation, and the use of the criteria highlights the importance of sustainability in supplier selection and order allocation. The methodology’s practicality is further supported by the analysis conducted in this study, which demonstrates the methodology’s ability to handle the uncertainties associated with supplier evaluation and selection. The proposed methodology offers a comprehensive approach to the SSOA problem that can effectively handle the uncertainties in supplier evaluation and selection and promote sustainable practices in supply chain management.

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Integrating IVFRN-BWM and Goal Programming to Allocate the Order Quantity Considering Discount for Green Supplier

Cited by 22 publications

References 69 publications

Energy Supply Chain Risk Evaluation based on a Two-Stage Decision Making Approach

Energy Supply Chain Risk Evaluation based on a Two-Stage Decision Making Approach

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

Sustainable Supplier Selection and Order Allocation Using an Integrated ROG-Based Type-2 Fuzzy Decision-Making Approach

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