HANDLING THE CHALLENGES OF A GREEN SUPPLY CHAIN IN THE CONTEXT OF PRODUCT BLENDING TRANSPORTATION WITHIN A NEUTROSOPHIC ENVIRONMENT

Abstract

The accelerated growth of economic activity and resource consumption underscores the urgent need to integrate sustainability into transportation systems. This paper explores the incorporation of sustainability into multi-product blending processes within these systems, focusing on several critical objectives: minimizing transportation costs – including variable expenses, fixed charges, and maintenance costs – carbon emissions, and product deterioration, while maximizing the volume of liquid transported and reducing transportation time. Real-world transportation scenarios are often complicated by data limitations, measurement inaccuracies, and uncertainties, which challenge effective decision-making. To address these challenges, this research introduces Neutrosophic Sets as a robust framework for managing uncertainty by capturing varying degrees of truth, falsity, and indeterminacy. The study employs a neutrosophic environment with Neutrosophic Goal Programming, Fuzzy Programming, and Two-Phase Programming methodologies to determine a compromise solution for the multi-objective transportation problem. The effectiveness of the proposed model is demonstrated through numerical simulations, with results compared to traditional methods. The paper concludes with a comprehensive sensitivity analysis and outlines future research directions, providing valuable insights into the optimization of sustainable transportation systems.