Decision-Making with Neutrosophic Set: Theory and Applications in Knowledge Management


Series: Computational Mathematics and Analysis

BISAC: MAT034000

This book introduces readers to the concept of the neutrosophic set which can deal with dynamic and complex decision-making problems. With the complexity of the socio-economic environment, today’s decision-making is one of the most notable ventures, whose mission is to decide the best alternative under numerous known or unknown criteria. This book provides a large amount of theoretical and practical information about the latest research in the field, allowing readers to gain an extensive understanding of both the fundamentals and applications of neutrosophic sets to solve different kinds of decision-making problems and mathematical programming such as medical diagnosis, pattern recognition, construction problems, technology selection etc.

Table of Contents


Section I: Mathematical Aspects of Neutrosophic Set

Chapter 1. Neutrosophic Set Theory and Engineering Applications: A Study
(Bhargavi K and B. Sathish Babu – Department of CSE, Siddaganga Institute of Technology, Tumakuru, Karnataka, India, et al.)

Chapter 2. A New Type of Quasi Open Functions in Neutrosophic Topological Environment
(M. Parimala, C. Ozel, F. Smarandache, M. Karthika – Department of Mathematics, Bannari Amman Institute of Technology, Sathyamangalam – Tamil Nadu, India, et al.)

Chapter 3. Accordance with Neutrosophic Logic? A Multimoora Approach for Countries Worldwide
(Brauers Willem K. M. – University of Antwerp, Department of Economics, Belgium, Prinsstraat, 13, 2000 Antwerpen)

Chapter 4. Evaluation of Online Education Software Under Neutrosophic Environment
(Fatma Kutlu Gündoğdu and Serhat Aydın – Industrial Engineering Department, National Defence University, Turkish Air Force Academy, 34149, Istanbul, Turkey)

Chapter 5. A New Attribute Sampling Plan for Assuring Weibull Distributed Lifetime Using Neutrosophic Statistical Interval Method
(P. Jeyadurga and S. Balamurali – Department of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil 626126, TN, India)

Section II: Decision Making Problems with Neutrosophic Set

Chapter 6. On Some Propositions of Boundary in Interval Valued Neutrosophic Bitopological Space
(Bhimraj Basumatary – Department of Mathematical Sciences, Bodoland University, Kokrajhar, BTAD, India)

Chapter 7. An Expected Value-Based Novel Similarity Measure for Multi-Attribute Decision-Making Problems with Single-Valued Trapezoidal Neutrosophic Numbers
(Palash Dutta and Gourangajit Borah – Department of Mathematics, Dibrugarh University, Dibrugarh, Assam, India)

Chapter 8. Trnn-Aras Strategy for Multi-Attribute Group Decision-Making (Magdm) in Trapezoidal Neutrosophic Number Environment with Unknown Weight
(Rama Mallick and Surapati Pramanik – Department of Mathematics, Umeschandra College, Kolkata, West Bengal, India, et al.)

Chapter 9. An Application of Reduced Interval Neutrosophic Soft Matrix in Medical Diagnosis
(Somen Debnath – Department of Mathematics, Tripura University, Suryamaninagar, Agartala, Tripura, India)

Chapter 10. Interval-Valued Neutrosophic N Soft Set and Intertemporal Interval-Valued Neutrosophic N Soft Set to Assess the Resilience of the Workers Amidst Covid-19
(V. Chinnadurai and A. Bobin – Department of Mathematics, Annamalai University, Tamilnadu, India)

Section III. Extension of the Neutrosophic Set

Chapter 11. 2-Additive Choquet Cosine Similarity Measures for Simplified Neutrosophic Sets and Applications to Medical Diagnosis
(Ezgi Türkarslan, Murat Olgun, Mehmet Ünver, Şeyhmus Yardimci – TED University, Faculty of Arts and Science, Department of Mathematics, Ankara, Turkey, et al.)

Chapter 12. Multi-Attribute Group Decision-Making Based on Uncertain Linguistic Neutrosophic Sets and Power Hamy Mean Operator
(Yuan Xu, Xiaopu Shang and Jun Wang – School of Economics and Management, Beijing Jiaotong University, Beijing, China, et al.)

Chapter 13. An N-Dimensional Neutrosophic Linguistic Approach to Poverty Analysis with an Empirical Study
(D. Ajay, J. Aldring and S. Nivetha – Assistant Professor, Department of Mathematics, Sacred Heart College (Autonomous), Tirupattur, Tamilnadu (State), India, et al.)

Chapter 14. Multi-Granulation Single-Valued Neutrosophic Hesitant Fuzzy Rough Sets
(Tahir Mahmood and Zeeshan Ali – Department of Mathematics & Statistics, International Islamic University Islamabad, Pakistan)


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