<p>In this paper, we propose a fully triangular intuitionistic fuzzy number model for the multi-objective transportation problem that successfully manages ambiguity and hesitation in decision making. To provide a reliable transportation plan in the case of unpredictability, the suggested methodology uses a multi-objective optimization framework that strikes a balance between cost, time and reliability. A significant component of this study is the weight assignment and multiple decision levels, which enables decision makers to rank goals and customize solutions according to specific transportation needs. This technique makes decision making easier while also provides flexibility in dealing with difficult real-world situations. Furthermore, we compare our proposed model with other approaches that are currently in use, such as the intuitionistic fuzzy approach and the goal programming approach. According to the outcomes, our model provides a more effective and realistic transportation strategy by offering a more balanced trade-off between cost, time and reliability. A numerical example is provided to illustrate the efficacy of the method, showing how combining centre, expected, and ranking values ​​increases solution accuracy and decision reliability while providing a systematic way of comparing and defuzzifying fuzzy numbers.</p>