Sanjay KumarJoshi, Dheeraj2018-12-212018-12-212018-01http://krishikosh.egranth.ac.in/handle/1/5810086174Multi-criteria group decision making (MCGDM) has various applications in many real life problems of banking, data mining, water resource location, human resource development, resource allocation and portfolio selection. The present research work mainly focus on development and implementation of MCGDM/MCDM models in the environment of uncertainty and hesitation. In this study, 6 different models of MCGDM methods are developed in interval-valued intuitionistic hesitant fuzzy (IVIHF), probabilistic hesitant fuzzy (PHF) and interval-valued intuitionistic hesitant fuzzy linguistic and uncertain linguistic environment. These models are based on entropy measure, distance and similarity measures. Cloud model based TOPSIS method and Choquet integral based TOPSIS methods are also developed to consider both randomness, fuzziness and interaction phenomenon in MCGDM problems. Model [1] is IVIHF entropy based MCGDM method. In this model criterion weights are determined using IVIHF entropy. Model [2] is probabilistic intuitionistic fuzzy information based TOPSIS method. In Model [3], a series of distance and similarity measures for probabilistic hesitant fuzzy set is defined and used in MCDM problem. In Model [4], a new class of fuzzy set called probabilistic hesitant fuzzy linguistic set is defined and used in MCGDM problem. In Model [2], Model [3] and Model [4] a real case study of stock selection problem has been taken for MCGDM methods. Model [5] is trapezium cloud based TOPSIS method for MCGDM and is used to rank different stocks on the basis of some financial criteria. Model [6] is Choquet integral based TOPSIS method in interval-valued intuitionistic hesitant fuzzy uncertain linguistic environment and deals with the situations where decision makers have hesitation in providing their preferences over objects in decision making. All developed models (Model [1-6]) are implemented on real life problems of stock selection problem, candidate selection problem and ranking of the organizations. To examine the validity of ranking results validity test of all models (Model [1-6]) under certain test criteria are also done along with comparative analysis. Simulation study of Model [2], Model [3] and Model [4] with similar real data set of seven organizations provides their different ranking. To further compare rankings of the organizations: Model [2-4] are implemented in portfolio selection problems to analyze portfolio risk and return.ennullThesis