Hesitant Fuzzy TOPSIS based Investment Projects Selection Problem

The present study develops a decision support methodology for investment projects selection problem. The proposed methodology applies the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach under hesitant fuzzy environment. Selection of investment projects is made considering a set of weighted attributes. To evaluate attributes our approach implies using of expertsu0027 assessments. In the proposed methodology the values of the attributes are given by group of experts in the form of lingual assessments - linguistic terms. Then, these lingual assessments are expressed in trapezoidal fuzzy numbers. Consequently, proposed approach is based on hesitant trapezoidal fuzzy TOPSIS decision-making model. The case when the information on the attributes weights is completely unknown is considered. The attributes weights identification based on De Luca-Termini information entropy is offered in context of hesitant fuzzy sets. Following the TOPSIS algorithm, first the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. An example is shown to explain the procedure of the proposed methodology.