An Approach to Transportation Problems Using Intuitionistic Quadripartitioned Neutrosophic Sets

Abstract

 In today's world, unpredictable economic and environmental factors make it difficult to estimate supply, demand, and transportation costs accurately. This study focuses on solving transportation problems where such uncertain data is expressed using intuitionistic quadripartitioned neutrosophic numbers (IQPNNs). These numbers offer a better way to handle complex uncertainty compared to traditional fuzzy numbers, which often fall short in dealing with high levels of indeterminacy and contradiction. To address this, we use intuitionistic quadripartitioned neutrosophic sets (IQPNSs), which provide a more powerful mathematical approach to manage unclear and conflicting information. A new algorithm is proposed to find the best transportation plan using operations on IQPNNs. A practical example is provided to show how the method works and to compare it with existing techniques. The results show that our IQPNS-based model improves accuracy, adaptability, and dependability in uncertain transportation situations. This work also opens up new possibilities for future research on improving transportation systems in uncertain environments.