Neutrosophic Multi Criteria Decision Making

This book is a printed edition of the Special Issue "Neutrosophic Multi-Criteria Decision Making" that was published in Axioms

In this paper, we propose a new hybrid neutrosophic multi criteria decision making (MCDM) framework that employs a collection of neutrosophic analytical network process (ANP), and order preference by similarity to ideal solution (TOPSIS) under bipolar neutrosophic numbers. The MCDM framework is applied for chief executive officer (CEO) selection in a case study at the Elsewedy Electric Group, Egypt. The proposed approach allows us to assemble individual evaluations of the decision makers and therefore perform accurate personnel selection. The outcomes of the proposed method are compared with those of the related works such as weight sum model (WSM), weight product model (WPM), analytical hierarchy process (AHP), multi-objective optimization based on simple ratio analysis (MOORA) and ANP methods to prove and validate the results.

Internet of Things (IoT) connects billion of devices to afford inventive opportunities between things and people. The rapid development of products related to IoT is a new challenge to keep security issues, lack of confidence, and understanding of IoT. Analytical hierarchy process (AHP) is a classic multi criteria decision making (MCDM) method used to analyze and scale complex problems and to obtain weights for the selected criteria. The vague and inconsistent information in real situations can lead to decision maker's confusion.

This book offers a comprehensive guide to the use of neutrosophic sets in multiple criteria decision making problems. It shows how neutrosophic sets, which have been developed as an extension of fuzzy and paraconsistent logic, can help in dealing with certain types of uncertainty that classical methods could not cope with. The chapters, written by well-known researchers, report on cutting-edge methodologies they have been developing and testing on a variety of engineering problems. The book is unique in its kind as it reports for the first time and in a comprehensive manner on the joint use of neutrosophic sets together with existing decision making methods to solve multi-criteria decision-making problems, as well as other engineering problems that are complex, hard to model and/or include incomplete and vague data. By providing new ideas, suggestions and directions for the solution of complex problems in engineering and decision making, it represents an excellent guide for researchers, lecturers and postgraduate students pursuing research on neutrosophic decision making, and more in general in the area of industrial and management engineering.

Decision making is a continuous and necessary part of the management of any organization or business activity. By solving the uncertain multi criteria decision making problems we can choose more reliably from the incomplete and complex information in real life dynamic from the decision makers. In this work, we discussed the PROMETHEE-II(Preference Ranking Organization Method For Enrichment Evaluation) for dealing with the Multi Criteria Decision Making problems with Single Valued Trapezoidal Neutrosophic Fuzzy Set in which the multiple alternatives are implemented by the decision makers with respect to the related criteria and the weights are completely unknown. Besides, the criteria weights are estimated based on the pairwise comparison of the criteria. By applying the PROMETHEE-II method, we get a partial and complete ranking order of the alternatives.

In this paper, a new extension of the crisp COPRAS method has been proposed. This extension is developed in the context of single value neutrosophic sets. The information processing flow has been proposed for the solution of the multicriteria decision-making problems.

Learning management systems (LMSs) are used today to assist in the designing, delivery and management of learning resources for learners. There are hundreds of LMS available in the marketplace. Selecting the most suitable LMS that meets specific requirements is a problem of decision making. Many studies in learning management system selection are implemented under complete information, while in the real world many uncertainty aspects do exist.

The aim of this paper is to introduce some new operators for aggregating single-valued neutrosophic (SVN) information and to apply them to solve the multi-criteria decision-making (MCDM) problems. Single-valued neutrosophic set, as an extension and generalization of an intuitionistic fuzzy set, is a powerful tool to describe the fuzziness and uncertainty, and Muirhead mean (MM) is a well-known aggregation operator which can consider interrelationships among any number of arguments assigned by a variable vector. In order to make full use of the advantages of both, we introduce two new prioritized MM aggregation operators, such as the SVN prioritized MM (SVNPMM) and SVN prioritized dual MM (SVNPDMM) under SVN set environment. In addition, some properties of these new aggregation operators are investigated and some special cases are discussed. Furthermore, we propose a new method based on these operators for solving the MCDM problems. Finally, an illustrative example is presented to testify the efficiency and superiority of the proposed method by comparing it with the existing method.