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In this study, we have proposed a supplier selection problem with the goals of minimizing the net cost, minimizing the net rejections, minimizing the net late deliveries, and minimizing the net green house gas emission subject to realistic constraints like suppliers’ capacity, buyer’s demand etc. Due to uncertainty, the buyer’s demand is fuzzy in nature and can be represented as a triangular neutrosophic number. We have also considered that quantity discounts are provided by the suppliers.
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.
Papers on neutrosophic statistics, neutrosophic probability, plithogenic set, paradoxism, neutrosophic set, NeutroAlgebra, etc. and their applications.
In this age of information, the industrial sectors are embedding its functioning principles with the components of Industry 4.0. This article proposes a production inventory model discussing the paradigm shift towards smart production process involving many new cost parameters in addition to the conventional inventory costs. The proposed Industry 4.0 production inventory model is discoursed and compared in both deterministic and neutrosophic environments. The trapezoidal neutrosophic number representation of the parameters enhances the efficiency of the model in determining the optimal order time that minimizes the total costs. The model is highly comprehensive in nature and it is validated with a numerical example.
This paper proposes an integrated multi-attribute border approximation area comparison (MABAC) based on the best-worst method (BWM), plithogenic set, and rough numbers. BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency. For the treatment of uncertainty, a plithogenic set and rough number (RN) are used to improve the accuracy of results. Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness. Then, based on the plithogenic aggregation and the results of BWM evaluation, we use MABAC to find the optimal alternative according to defined criteria. To examine the proposed integrated algorithm, an empirical example is produced to select an optimal supplier within five options in the healthcare industry.
This paper introduces the concept of saturated refined neutrosophic sets and extends the same to the special kinds of neutrosophic sets. The proposed concept is applied in decision making on Teacher’s adaptation to cybergogy. The decision making environment is characterized by different types of teachers, online teaching skills and various training methods. Fuzzy relation is used to match the most suitable method to the different kinds of teachers with the intervention of saturated interval valued neutrosophic refined oversets, offsets and undersets. The results obtained by applying the notion of saturated refined sets using various distance measures represent the effect of training methods on teacher’s adaptation to learner-centred teaching methods, which certainly give space to gain many insights on the relationship between quality of training and teacher’s adaptation rate. The proposed concept has wide scope and few limitations.
With increasing global concerns toward environmental protection and sustainable development, green supply chain management (GSCM) has drawn much attention from academicians and practitioners. Selecting an optimal green supplier is a critical part of GSCM, which can be viewed as a kind of multi-criteria decision making (MCDM) problem. To derive the best result, large group of decision makers are often involved in the green supplier selection nowadays. Besides, decision makers tend to express their evaluations utilizing uncertain linguistic terms due to the vagueness of human thinking. Hence, this paper aims to propose a hybrid MCDM approach for green supplier selection within the large group setting. More concretely, interval-valued intuitionistic uncertain linguistic sets (IVIULSs) are applied for assessing the performance of green suppliers concerning each criterion. Ant colony algorithm is utilized to cluster decision makers into several subgroups. The linear programming technique for multidimensional analysis of preference (LINMAP) is adopted for the determination of the optimal weights of criteria objectively. Finally, an extended MULTIMOORA approach is utilized to generate the ranking of alternative suppliers. The practicality and usefulness of the developed large group green supplier selection framework is illustrated using an empirical example of a real estate company.