A Group Decision Approach for Supplier Selection Problem Based on a Multi-criteria Model

Rădulescu, Constanţa Zoie; Rădulescu, Marius

doi:10.24846/v29i1y202004

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…The supplier selection problem was applied with 3 main and 16 sub-criteria. In the study, the most important criteria in SSS for medical devices were determined as accuracy, trust and safety, response time, precision, and provider reputation [25]. A study was conducted to determine the most suitable supplier for hospitals.…”

Section: Factors For Incrementing Sustainability Of Healthcare Supply...mentioning

confidence: 99%

A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0

2022

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The COVID-19 pandemic has led to major disruptions in workflows across all industries. All sectors are trying to sustain operations during this extremely difficult time and the healthcare sector is the most important of them. It is unthinkable to stop the operations of the health system because it serves human life. Health institutions must supply the products such as masks, gloves, and ventilators subject to service on time for certain activities to continue indefinitely under all conditions. By adopting modern logistics activities and technologies, healthcare organizations can provide sustainable diagnosis and treatments to patients by automating their various operations. With the COVID-19 pandemic, how to select an appropriate sustainable supplier has become an important task in the era of Logistics 4.0. From this viewpoint, a sustainable supplier selection framework is implemented for a health institution under the effect of the pandemic. To determine the direct effects of the pandemic in the health sector, fuzzy Multi-Criteria Decision-Making (MCDM) methods are utilized in the application. After a thorough review of the literature and interviews with experts, the criteria are organized in a comprehensive hierarchical structure. The fuzzy Best-Worst Method (F-BWM) technique is employed to find the weights for the determined criteria. Consequently, the fuzzy Additive Ratio Assessment Method (F-ARAS) method was applied to rank the alternative suppliers. In addition, with a comprehensive sensitivity analysis, alternative situations are examined against possible breaks in the supply chain. Thus, from the perspective of Logistics 4.0 and sustainability, this study contributes to the literature with an analysis of the health system’s survival in difficult and fragile periods, such as COVID-19. Investigating the importance of SSS can be a road map for the policymakers and the decision-makers is beneficial since the impact of COVID-19 on SSS is studied from the perspective of Logistics 4.0.

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Section: Factors For Incrementing Sustainability Of Healthcare Supply...mentioning

confidence: 99%

A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0

2022

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“…Farenzena, et al (2010) presented a symmetry-driven accumulation of local features (SDALF) method with symmetry and asymmetry to address viewpoint variability. The metric system is a very important element in person Re-ID, and many methods have been applied in computer vision and proved to be effective (Subotic et al, 2020, Yousuf Uddin et al, 2021, Rădulescu & Rădulescu, 2020, 2021b, Ma et al, 2020, for example, Keep It Simple and Straightforward Metric learning (KISSME) (Kostinger et al, 2012), Locally-Adaptive Decision Function (LADF) (Li et al, 2013) and Cross-View Quadratic Discriminant Analysis (XQDA) (Liao et al, 2015). These algorithms have shown excellent results in face recognition and person Re-ID.…”

Section: Introductionmentioning

confidence: 99%

Fused-Grain Feature Learning for Unsupervised Person Re-identification

Han¹,

Huang²,

Zhang³

et al. 2022

STUD INFORM CONTROL

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Most supervised learning methods are currently used to solve the task of person re-identification (Re-ID) and yield excellent results. But these methods usually need manual annotation of training data. Especially for large data sets, they need too high cost of manual annotation and the data are difficult to obtain for fully pairwise labeling. So unsupervised learning becomes a necessarily trend for person Re-ID. This paper is trying to solve the problem by unsupervised learning method. Moreover, global features focus on spatial integrity of person features, and local ones help to highlight discriminative features of different patches. Therefore, fused-grained unsupervised (FGU) learning framework of global and local branches' feature learning is proposed to solve Re-ID task. Specifically, for the local branch, one extracts patches from a feature map which learned on a PatchNet network of images, and learns their fine-grained features to pull close the similar patches and push away the dissimilar ones. For the global branch, one maximizes the diversity between classes by repelled loss and similarity within classes through attracted loss, then similarity and diversity in the unlabeled data sets are used as information for unsupervised cluster merging and learning their coarse-grained features. The two branches are used to jointly achieve the effect of increasing inter-class differences and intra-class similarity. A large number of experiments verify the superiority of the proposed method for unsupervised person re-identification.

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“…Scholars used Delphi method and Lichter scale to construct a risk maturity assessment model to evaluate the risk management maturity of suppliers in the automotive industry [1]. Some scholars established a minimum risk model with budget and performance constraints with the goal of minimizing risks, and studied the group decision method for supplier selection [24]. Scholars combined fuzzy analytic hierarchy Process (AHP) with fuzzy multiplicative multi-objective optimization based on ratio analysis, and proposed a comprehensive method of risk assessment and supplier selection [14].…”

Section: Introductionmentioning

confidence: 99%

Risk Evaluation and Selection of Lithium Power Battery Suppliers for New Energy Vehicles Based on TRIT Method

Hua¹,

Yu²,

Liang³

2022

Proceedings of the 2022 3rd International Conference on Management Science and Engineering Management (ICMSEM 2022)

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Aiming at the problem of power battery suppliers evaluation and selection from the perspective of risk, a two-stage risk assessment and selection model was constructed based on Trust Risk and Improved TOPSIS (TRIT method) focusing on lithium power battery suppliers to achieve the goal of improving the reliability of evaluation results and decision-making efficiency. Firstly, a preliminary screening model of suppliers evaluation under the influence of trust risk is established. Secondly, experts with high consensus degree preference are organized to form an internal low-risk decision-making team. Thirdly, a risk evaluation indexes system containing reverse logistics capability risk is established and the indexes weights are determined by fuzzy AHP method. Then, the improved TOP-SIS method is introduced in the secondary screening to evaluate the risk status of different suppliers, and the ranking results of the risk size of different suppliers are obtained, so as to assist enterprises to choose cooperation partners more scientifically and efficiently. Finally, taking the risk evaluation and selection of lithium battery suppliers of a new energy vehicle manufacturer as an example, the final selection results are analyzed and verified the feasibility and effectiveness of the proposed method.

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A Group Decision Approach for Supplier Selection Problem Based on a Multi-criteria Model

Cited by 5 publications

References 16 publications

A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0

A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0

Fused-Grain Feature Learning for Unsupervised Person Re-identification

Risk Evaluation and Selection of Lithium Power Battery Suppliers for New Energy Vehicles Based on TRIT Method

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