Novel sustainable green transportation: A neutrosophic multi-objective model considering various factors in logistics

Growing environmental concerns are driving the logistics operations in industry towards sustainable practices, known as green logistics. Optimizing transportation for solid goods are facing challenges to handle complex issues, though traditional methods are often focusing only on single objective like minimizing cost or maximizing the profit. However, to overcome all the possible challenges based on recent requirements, the multi-objective solid transportation problems (MOSTPs) will handle effectively by considering environmental factors like carbon emissions alongside cost and travel time. This research study contributes to the development of robust and eco-friendly transportation solutions by providing a framework for handling uncertainties in MOSTPs. Further, the model influenced in the neutrosophic set (NS) theory, which is an emerging tool to address inherent uncertainties in real-world data associated with environmental impacts and resource limitations. The NS theory incorporates truth-membership, indeterminacy, and falsity-membership functions, allowing for effective modeling of ambiguity. This model presents a Multi-Objective Fixed Charge Solid Transportation Problem (MOFCSTP) using a bi-polar single-valued neutrosophic set to handle all these uncertainties related to green sustainable transportation. Further, different approaches for achieving optimal solutions are explored, including Neutrosophic Compromise Programming Approach (NCPA), M-Pareto Optimal Solution Approach (M-POSA), Weighted Sum Method (WSM), Neutrosophic Goal Programming (NGP), Neutrosophic Global Criterion Method (NGCM), and Fuzzy Goal Programming (FGP). Lastly, the obtained results are then discussed and compared with sensitivity analysis, which is conducted to evaluate the strengths and limitations of each method to justify the effectiveness of the model.