الفهرس 
CHAPTER 1 INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
In the last few decades, the Multi-Criteria group Decision Making (MCGDM) Problems have widely spread. This type of problems attracted researchers for their importance in making appropriate decisions and solving many of decision-making problems. MCGDM problems are marked by the presence of a decision-making group, which complicate the problem solution due to their different attitudes, views, and trends. The main challenges emerged in solving the MCGDM problems are summarized
in three points. Firstly, the uncertainty in data obtained by the decision makers for the
assessments of the criteria and the alternatives. Secondly, the insufficient weight
information of the criteria as these weights may be completely unknown or partially
known. Finally, the emergence of competition in the case of more than one participant
in the problem, each of them wish to gain the best solution.
This thesis introduces different proposed techniques to overcome the challenges that encounter the solution of the MCGDM problems and obtain the best possible solution for all test cases under consideration. The data uncertainty is handled by using Single-Valued Neutrosophic sets (SVNs). Three different proposed methods are introduced to determine the unknown criteria weights for either the completely unknown or the partially known weights. These methods are applied individually with the Neutrosophic TOPSIS and the Neutrosophic VIKOR for solving the MCGDM problems and ranking the alternatives. Integration between GRA method and the method of maximizing deviation in two different ways, namely; MDGRA and MDGRAAgg, is also proposed to solve the MCGDM problems. Neutrosophic sets are utilized in conjunction with the game theory to solve the competitive MCGDM problems. Finally, the experimental results corroborated the applicability and effectiveness of the proposed techniques.