Providing A Compromise Decision-Making Based On The Modified VIKOR Under Uncertainty: An Intuitionistic Trapezoidal Fuzzy Set

Decision-making is a mental process which all human bodies involve it during their life. Decision-making process is performed along with individual`s culture, perceptions, beliefs and values, attitude, personality and knowledge, and these factors influence each other mutually. Decision-making is one of the most important tasks of management, and one of the main success reasons of individuals and organizations is proper decision-making. So the necessitate of scientific methods which help human in this field is completely tangible. Decision-making can be performed in different situation, some situation which can be exact or non-exact based on problem data. An example of decision-making in uncertainty is deciding in fuzzy situation. Fuzzy theory generally focused on analysing vague and sealed data. In mathematic classic logic, value of a proposition defined by “1” if it is true and “0” id it is wrong. In fuzzy logic this value is real which selected in [0,1]. This value or correctness can be called correctness degree. Atanassov added another real value between [0,1] in term of lack of correctness degree, which these categories are called intuitive fuzzy categories. In this thesis, a compromising solution is [resented based on revised VIKOR method which presented by Vahdani et al.(2013), in a situation which problem data are trapezoidal and in an intuitive fuzzy environment. Then this solution implemented on two numerical problems. Sensitivity analysis conducted on each problem and finally alternatives ranked according to criteria