Transportation strategy decision-making process using interval-valued complex fuzzy soft information

Transportation is among the more vital economic activities for a business and our daily life actions. At present, transport is one of the key branches playing a crucial role in the development of the economy. Transportation decision-making looks for ways to solve current and anticipated transportation problems while avoiding future problems. An interval-valued complex fuzzy set (IVCFS) is an extended form of fuzzy, interval-valued fuzzy and complex fuzzy sets, and it is used to evaluate complex and inaccurate information in real-world applications. In this research, we aim to examine the novel concept of IVCF soft relations (IVCFSRs) by utilizing the Cartesian product (CP) of two IVCF soft sets (IVCFSSs), which are determined with the help of two different concepts, referred to as IVCF relation and soft sets. Moreover, we investigated various types of relations and also explained them with the help of some appropriate examples. The IVCFSRs have a comprehensive structure discussing due dealing with the degree of interval-valued membership with multidimensional variables. Moreover, IVCFSR-based modeling techniques are included, and they use the score function to select the suitable transportation strategy to improve the value of the analyzed data. Finally, to demonstrate the effectiveness of the suggested work, comparative analysis with existing methods is performed.

Automated summary

Transportation is a vital economic activity in both business and daily life, and its decision-making process seeks to address current and future transportation problems. This research focuses on the novel concept of interval-valued complex fuzzy sets (IVCFS) and IVCF soft relations (IVCFSRs) to improve transportation strategies. The effectiveness of the suggested work is demonstrated through comparative analysis with existing methods.