Handling the challenges of a green supply chain in the context of product blending transportation within a neutrosophic environment

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.