Sustainable supplier selections have been improved by an increased number of multi-criteria group decision-making methods and techniques. This thesis provides a multi-criteria group decision-making technique of the analytical network process method and the VIKOR (ViseKriterijumska Optimizacija I Kompromisno Resenje) method under neutrosophic environment for dealing with incomplete information and high order imprecision. Also, to attain competitive advantages and promote environmental performance, a proactive approach called green supply chain management (GSCM), has been extensively employed. In this thesis, we use the robust ranking technique with neutrosophic set to handle practices and performances in GSCM. We evaluate GSCM practices using the robust ranking technique in order to detect practices leading to better economic and environmental performances. We employ the neutrosophic set theory to handle vague data, imprecise knowledge, incomplete information and linguistic imprecision. The present thesis employs the neutrosophic set for decision making and evaluation method to analyze and determine the factors influencing the selection of supply chain management suppliers. For any organization, the selection of suppliers is a very important step to increase productivity and profitability. Any organization or company seeks to use the best methodology and the appropriate technology to achieve its strategies and objectives. Moreover, this thesis proposes an advanced type of neutrosophic technique, called type 2 neutrosophic numbers, and defines some of its operational rules. The type 2 neutrosophic number weighted averaging operator is determined in order to collective the type 2 neutrosophic number set, inferring some properties of the suggested operator. The operator is employed in a multi attribute decision making problem to collect the type 2 neutrosophic numbers based classification values of each alternative over the features. The convergent classification values of every alternative are arranged with the assistance of score and accuracy values with the aim to detect the superior alternative. We introduce an illuminating example to confirm the suggested approach for multi attribute decision making issues, ordering the alternatives based on the accuracy function. Selecting an appropriate alternative among the selection options is a difficult activity for decision makers, since it is complicated to express attributes as crisp numbers.