A Scenario-based Multi-Attribute Method for Alternatives Ranking Problem Using a Neutrosophic Similarity Measure

Public-Private Partnership (PPP) improves the procurement of public yields with fewer public resources and private involvement. A fundamental problem in PPP projects is choosing a suitable private partner, which determines the success or failure of the project. Multi-attribute decision-making methods have been applied to select a private sector partner. These approaches can examine several quantitative and qualitative indicators simultaneously. All these models form the decision matrix based on the judgments of experts who exploit past or present information. Despite considering the complexity of the problem, common approaches employed in decision-making literature are incapable of facing uncertainty. Researchers have used fuzzy sets and fuzzy set extensions to solve this fundamental problem. Nevertheless, future uncertainty that can occur under the influence of changes in environmental indicators has been overlooked in this context. Accordingly, intending to answer the uncertainty problem in this research, we designed future scenarios based on the most critical criteria mentioned in the literature. We evaluated the performance of alternatives by considering key indicators. We also used Neutrosophic sets to explain the opinions of experts more precisely. The methodology was described using a numerical example, and the step-by-step implementation of the approach was introduced. Utilizing the proposed method supports decision-makers in considering the problem's complexity and uncertainty.

Keywords:

Decision-making , MADM , Scenario , Neutrosophic Sets , Similarity Measure , Public-Private Partnership , Ranking