Proposing a new methodology for prioritising the investment strategies in the private sector of Iran (original) (raw)
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Fuzzy multi-attribute evaluation of investments
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The work proposes an approach for solving a multiple-attributes decision making (MADM) problems in hesitant fuzzy environment based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. 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. In the TOPSIS method the ranking of alternatives is made in accordance with the proximity of their distance to the positive and negative ideal solutions. The developed approach is applied to evaluation of Investment Projects with the aim of their ranking and identification of high-quality projects for investment.
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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 experts' 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 th...
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