Single-valued neutrosophic dynamic aggregation information with time sequence preference for IoT technology in supply chain management

Abstract

The Internet of thing (IoT) is a global platform for connecting intelligent objects over the Internet. It facilitates the integration of the “supply chain (SC)” and “information and communication technology (ICT)” infrastructures inside a company and with its vendors and clients. The “supply chain management (SCM)” is presently required if a firm wishes to keep up with the rapid evolution of its consumers’ needs. Several research has demonstrated that manufacturing companies must expedite the transition of their attention to sustainable development and the application of innovative technologies, such as IoT, in order to achieve their organizational objectives most efficiently. This study intends to examine the IoT’s applicability in SCM and assess the most popular IoT systems. The difficulty of identifying the best suitable IoT system is dependent on a multitude of variables, which are sometimes stated as incomplete and unreliable estimations. In order to reach an outcome, this paper proposes a multi-criteria paradigm for IoT solution selection in a single-valued neutrosophic environment. Single-valued neutrosophic set (SiVNS) is a strong model to address uncertain information in terms of three membership functions, namely indeterminacy, truthfulness, and falsity. The goal of this study is to introduce some dynamic single-valued neutrosophic aggregation operators (AOs) for multi-period decision-making problems that involve uncertain single-valued neutrosophic information. We develop novel Einstein AOs named as “dynamic single-valued neutrosophic Einstein weighted averaging (DSiVNEWA) operator and dynamic single-valued neutrosophic Einstein weighted geometric (DSiVNEWG) operator”. Several characteristics of the suggested AOs are investigated. Additionally, we develop a multi-stage dynamic decision analysis utilizing ideal solutions. To illustrate the proposed technique, a numerical example is presented. Comparison and authenticity analyses are conducted to ascertain the efficacy and superiority of the suggested multi-stage dynamic decision analysis in the practical situation.