Innovative pythagorean entropy measure with real world applications
Multi criteria decision-making is always required in almost every field. There are two major concerns in decision environment, one is uncertainty and other is complexity of the problem. To handle uncertainty, researchers have proposed a range of fuzzy sets. Uncertainty measures are good tool to handle information, specially, entropy measure is widely used to predict uncertain and vague information. Researchers have proposed several multi criteria decision making methods in literature to breakdown the complex problem and find the best possible solution. Technique for order preference by similarity to an ideal solution (TOPSIS) method is popularly known to rank all the alternatives. TOPSIS method is used extensively to solve real-life problems.
In this paper, a new Pythagorean fuzzy entropy measure is proposed. To demonstrate the benefits of proposed entropy measure, a comparison analysis with the most recent and relevant Pythagorean fuzzy entropy has been done. Moreover, TOPSIS method is also modified according to the proposed entropy measure in Pythagorean environment. Further, proposed methodology has been verified through real- life examples.The Modified TOPSIS approach is proven to be as efficient as the other methods. These findings demonstrate that the proposed strategy is applicable to real-world challenges. Result analysis is also included in this work.