During past few decades, fuzzy decision is an important attention in the areas of science, engineering, economic system, business, etc. To solve day-to-day problem, researchers use fuzzy data in transportation problem for presenting the uncontrollable factors; and most of multi-objective transportation problems are solved using goal programming. However, when the problem contains interval-valued data, then the obtained solution was provided by goal programming may not satisfy by all decision-makers. In such condition, we consider a fixed-charge solid transportation problem in multi-objective environment where all the data are intuitionistic fuzzy numbers with membership and non-membership function. The intuitionistic fuzzy transportation problem transforms into interval-valued problem using \((\alpha ,\beta )\)-cut, and thereafter, it reduces into a deterministic problem using accuracy function. Also the optimum value of alternative corresponds to the optimum value of accuracy function. A numerical example is included to illustrate the usefulness of our proposed model. Finally, conclusions and future works with the study are described.

在过去的几十年中，模糊决策一直是科学，工程，经济体系，商业等领域的重要关注点。为了解决日常问题，研究人员在运输问题中使用模糊数据来表示不可控制的因素。目标规划解决了大多数多目标运输问题。但是，当问题包含区间值数据时，则目标编程可能无法满足所有决策者提供的目标解决方案。在这种情况下，我们考虑了多目标环境中的固定电荷固体运输问题，在该环境中所有数据都是具有隶属度和非隶属度函数的直觉模糊数。直觉模糊运输问题使用\（（\ alpha，\ beta）\）转换为区间值问题-cut，然后，使用精度函数将其简化为确定性问题。另外，替代的最佳值对应于精度函数的最佳值。包含一个数值示例，以说明我们提出的模型的实用性。最后，描述了研究的结论和未来的工作。