Transshipment problems are special type of transportation problems in which goods are transported from a source to a destination through various intermediate nodes (sources/destinations), possibly to change the modes of transportation or consolidation of smaller shipments into larger or deconsolidation of shipments. These problems have found great applications in the era of e-commerce. The formulation of transshipment problems involves knowledge of parameters like demand, available supply, related cost, time, warehouse space, budget, etc. However, several types of uncertainties are encountered in formulating transshipment problem mathematically due to factors like lack of exact information, hesitation in defining parameters, unobtainable information or whether conditions. These types of uncertainty can be handled amicably by representing the related parameters as intuitionistic fuzzy numbers. In this article, a fully fuzzy transshipment problem is considered in which the related parameters (supply, demand and cost) are assumed to be represented as trapezoidal intuitionistic fuzzy numbers. The proposed method is based on ambiguity and vagueness indices, thereby taking into account hesitation margin in defining the values precisely. These indices are then used to rank fuzzy numbers to derive a fuzzy optimal solution. The technique described in this paper has an edge as it directly produces a fuzzy optimal solution without finding an initial basic feasible solution. The method can easily be employed to fuzzy transshipment problems involving trapezoidal intuitionistic, triangular intuitionistic, trapezoidal, triangular, interval valued fuzzy numbers and real numbers. The proposed technique is supported by numerical illustrations and it has been shown that the method described in the paper is computationally much more efficient than already existing method and is applicable to a larger set of problems.

转运问题是一种特殊的运输问题，其中货物通过各种中间节点（源/目的地）从源头运输到目的地，可能会改变运输方式或将较小货物的合并方式转变为较大货物或拆解货物。这些问题已在电子商务时代得到了广泛的应用。转运问题的制定涉及诸如需求，可用供应，相关成本，时间，仓库空间，预算等参数的知识。但是，由于缺乏准确信息，犹豫等因素，在数学上制定转运问题时会遇到几种不确定性在定义参数，无法获得的信息或是否有条件时。通过将相关参数表示为直觉模糊数，可以友好地处理这些类型的不确定性。在本文中，考虑了一个完全模糊的转运问题，其中相关参数（供应，需求和成本）被假定为梯形直觉模糊数。所提出的方法基于模糊度和模糊度指标，从而在精确定义值时考虑了犹豫余量。这些索引然后用于对模糊数进行排序，以得出模糊的最优解。本文描述的技术具有优势，因为它直接产生了模糊的最优解而没有找到初始的基本可行解。该方法可以轻松地用于涉及梯形直觉，三角形直觉，梯形，三角形，区间值模糊数和实数。所提出的技术得到了数字插图的支持，并且已经表明，与现有方法相比，本文中描述的方法在计算上效率更高，并且适用于更多问题。