In a managerial position, the ultimate objective is to take the right decision for the decision maker (DM) when transportation parameters are uncertain due to the globalization and other uncontrollable influences. In this paper, fuzzy membership function tactic based on goal programming to obtain the desired compromise solution of a multi-objective transportation problem (MOTP) in uncertain environment is proposed where the DM can choose a confidence level for different parameters. On the basis of DM’s choice on a particular confidence level, a compromise solution is obtain indicating the satisfaction level of the DM if the problem is feasible for this chosen confidence level. Uncertain normal distribution is used to convert the parameters from uncertain to a certain one. Simple linear programming problem (LPP) is designed using fuzzy linear membership function where the upper and lower values of the objectives are the desired goals of the DM. A numerical illustration is furnished to establish the effectiveness of the designed model whereas the single objective transportation problems are solved by TORA and LPPs are solved by using LINGO for operations research.

在管理职位上，最终目标是在运输参数由于全球化和其他不可控制的影响而不确定时，为决策者（DM）做出正确的决策。本文提出了一种基于目标规划的模糊隶属函数策略，以获得不确定环境下多目标运输问题（DM）可以选择不同参数的置信度的期望的折衷解。根据DM在特定置信度级别上的选择，如果问题对于该所选置信度水平可行，则将获得折衷解决方案，以表明DM的满意度。不确定的正态分布用于将参数从不确定的参数转换为特定的参数。使用模糊线性隶属函数设计简单线性规划问题（LPP），其中目标的上限值和下限值是DM的期望目标。提供了一个数值示例来证明所设计模型的有效性，而TORA可以解决单个目标运输问题，而LINGO可以用于运筹学来解决LPPs。