Informatica

Multi-Criteria Decision-Making (MCDM) is a vital tool for handling complex decision problems under uncertainty. Fuzzy set theory and its extensions, such as Single-Valued Neutrosophic Sets (SVNS), enhance decision-making by addressing ambiguity, indeterminacy, and partial information. Among MCDM techniques, TOPSIS has gained prominence for ranking alternatives, and its integration with some MCDM approaches has been widely applied. However, no prior study has combined the Analytic Hierarchy Process (AHP) with Neutrosophic-TOPSIS. This study proposes a hybrid AHP-SVNS-TOPSIS framework, where AHP determines the weights of evaluation criteria, and Neutrosophic-TOPSIS ranks alternatives under uncertain conditions. The model is applied to assess hydropower plant (HPP) performance, considering impacts from urbanization, climate change, and machine failures. The generator’s efficiency is the most important parameter, based on the results of the suggested model. Existing research validates the outcomes of the suggested model.

The paper develops the idea of valuation capital market regulations efficiency. The performance and efficiency measurement idea is very widely spread in the private sector. However efficiency concept in a public sector is rather new approach and still underdeveloped. The goal of this paper is to reveal the possibilities to measure the efficiency of a public sector performance by applying some descriptive dependencies systems and by using the capital market regulations as an example to disclose the possible outcomes of that analysis process.