Complex fuzzy intelligent decision modeling for optimizing economic sustainability in transportation sector

Abstract

AbstractThis paper introduces the concept of complex quadratic Diophantine fuzzy sets (CQDFS) which serves as a robust framework for effectively dealing with uncertainty within decision-making challenges. The study comprehensively explores the properties and characteristics of CQDFS by conducting a systematic comparative analysis to demonstrate its superiority over existing techniques in managing complex fuzzy information. This foundation contributes to the theoretical understanding of CQDFS and also provides valuable practical insights into a wide range of transportation strategies and economic efficiency. These insights offer practical solutions to enhance decision-making within these important and interconnected domains. The proposed complex information system serves as a versatile and adaptive tool, significantly strengthening the flexibility available for addressing complex decision-making challenges, particularly in contexts such as the management of GPS-enabled cargo vehicles and cargo loading operations, where precision and efficiency are of great importance.