Decision-making algorithm based on the energy of interval-valued fuzzy soft sets
This work addresses uncertainty in decision-making for domains like AI or data analysis, but it appears incremental as it builds on existing fuzzy set and soft set theories.
The paper tackled decision-making under uncertainty by introducing an energy-based algorithm for interval-valued fuzzy soft sets, demonstrating its application through examples and comparing it with existing methods.
In our work, we continue to explore the properties of interval-valued fuzzy soft sets, which are obtained by combining interval-valued fuzzy sets and soft sets. We introduce the concept of energy of an interval-valued fuzzy soft set, as well as pessimistic and optimistic energy, enabling us to construct an effective decision-making algorithm. Through examples, the paper demonstrates how the introduced algorithm is successfully applied to problems involving uncertainty. Additionally, we compare the introduced method with other methods dealing with similar or related issues.