Identification of Delay-Tolerant Networking by Employing MABAC Technique Based on Bipolar Complex Fuzzy Dombi Heronian Mean Operators

This work proposes a hybrid decision making model for dynamic and irregularly connected communication systems called Delay-Tolerant Networks (DTNs). A resilient and adaptable network allows for communication in an environment where traditional networks may fail to operate effectively. The main significance of this system is that it is commonly utilized in such scenarios where traditional networks are impractical, such as remote areas, disasterstricken regions, space missions, and military operations. The proposed model includes the “Multi-Attributive Border Approximation Area Comparison” (MABAC) method, together with Bipolar Complex Fuzzy Dombi Heronian Mean(BCFDHM) operators. To take the positive as well as negative attributes’ evaluations into consideration in complicated fuzzy environments, we use an enriched aggregation structure for the criteria, which incorporates the relationship between criteria through the Heronian mean function. Due to this, the MABAC technique within BCF information is more advanced and better than classical MABAC techniques in various models. After that, with the help of these enriched aggregation structures, we successfully identify and rank alternatives for DTN in an uncertain, imprecise, and bipolar condition. By employing the MABAC technique for the DTN system, we find the best and better alternative to the DTN system, which is Ã4 as mentioned below in section 4. At last, we compare our initiated work with many existing theories to prove the authenticity of the suggested work.