<p>The blending of products in transportation problems is an essential process that improves supply chain operations, reduces overall costs, offers more satisfaction to the customers, and is environment-friendly. Optimization techniques allows businesses to achieve critical benefits, from top-level performance improvements to increased competitive advantages. This paper introduces a new multi-objective 4D product blending transportation problem. It optimizes economic cost, customer satisfaction, carbon emissions, and product quality simultaneously. This model envisages bringing in concepts of sustainability in tune with global development goals related to the balance between economic, environmental, and qualitative aspects. The model further introduces a cost structure that is lower when the shipment quantity is high; it does this by incentive’s bulk transportation and offering cost efficiencies to customers. The expected value and a set level of chance constraint is used to change the model into a deterministic form and hence more reliable in the making of decisions. In solving this deterministic model, we shall employ the four advanced methods: fuzzy programming technique, intuitionistic fuzzy programming technique neutrosophic programming approach and two phase programming approach. Each technique uses its strategies to solve multi-objective optimization trade-offs. The best solutions obtained give a range of good options that can help the decision-makers balance different goals. The attraction of this study is to analyze multi objective 4D product blending transportation problem under intuitionistic fuzzy environment for a transportation system. A real-life numerical problem has been given and solved to prove the idea, comparing results with other existing methods.</p>