A mathematical model to the inadequacy of bipolar soft sets in uncertainty environment: N-polar soft set

Bipolar soft set is an extended model of soft set. However, as in soft set theory, this theory can also leave mismatched objects in the universe set for a parameter set. In this paper, our aim is not to leave unmatched objects in the universe set for each parameter set. Thus, we have information about every object in the universe set and it becomes easier to get better approaches to uncertainty problems. For this, we have defined N-polar soft sets and some properties and several theoretical operations of N-polar soft sets are given. In addition to these, an algorithm is given on how to determine the value N for any uncertainty problem. Next, two decision-making algorithms based on N-polar soft sets are proposed. Finally, a detailed analysis was made by comparing some of the important algorithms previously studied with the algorithms we suggested in our paper.

Automated summary

This paper introduces the theoretical model of N-polar soft sets, including their properties and operations, and proposes decision-making algorithms based on N-polar soft sets. The results show that using N-polar soft sets can provide better solutions to uncertainty problems.