الفهرس 
Title : A unified approach for uncertain multi-criteria decision making
ContantsOnly 14 pages are availabe for public view
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Abstract
In the real world, determining the exact values for multi-criteria decision making (MCDM) problems is difficult or impossible and their values can be considered as uncertain data. These problems become more complex when performances are associated with uncertainty. This thesis introduces a new approach to handle the different types of uncertainty in MCDM problems. To achieve this objective, the thesis proposes five MCDM methods, which are, multi-objective optimization on the basis of simple ratio analysis (MOOSRA), operational competitiveness rating analysis (OCRA), additive ratio assessment (ARAS), simple additive weighting (SAW) and multi objective and optimization on the basis of ratio analysis (MOORA) based on uncertain set theories. These theories are fuzzy set, rough set and grey set. Each method obtains the final ranking of the alternatives under an uncertain theory and selects the best one. All the proposed methods are implemented using an EXCEL worksheet. According to the new trend for assigning weights in multi-criteria decision making (MCDM) when no preference exits, this thesis proposed novel combinations of different weighting methods based on subjective and objective weights allocation that used to compute the weights of evaluation criteria. Rough Interval multi objective and optimization on the basis of ratio analysis (RIMOORA) is proposed to solve the group decision making problems in rough interval. This proposed method determines the most preferable alternative among all possible alternatives, when performance ratings are described by rough interval. The results show that, the proposed methods are applicable when large numbers of alternatives and criteria because they are direct and cause no complication in the calculation despite of the large-scale data. Also, the proposed methods are simple, effective and easy to calculate