This paper considers a shortest path problem in an imprecise and random environment. The edges in the network represent the approximate time required to cover the distance from one vertex to another vertex while the traffic conditions change randomly for each edge. The approximate time has been defined by using trapezoidal fuzzy number whereas the traffic conditions has been defined in linguistic term. Such type of network problem can be called as Fuzzy Stochastic Shortest Path Problem (FSSPP) in imprecise and random environment. In order to solve the model, a method has been proposed based on the Dijkstra’s algorithm and some numerous example have been solved to present its effectiveness.

本文考虑了在不精确随机环境中的最短路径问题。网络中的边缘表示覆盖一个顶点到另一个顶点的距离所需的大概时间，而流量条件对于每个边缘来说都是随机变化的。使用梯形模糊数定义了近似时间，而使用语言术语定义了交通状况。在不精确和随机的环境中，这种类型的网络问题可以称为模糊随机最短路径问题（FSSPP）。为了求解该模型，提出了一种基于Dijkstra算法的方法，并通过大量实例说明其有效性。