Shortest path problem (SPP) is a fundamental and well-known combinatorial optimization problem in the area of graph theory. In real-life scenarios, the arc weighs in a shortest path of a network/graph have the several parameters which are very hard to define exactly (i.e., capacity, cost, demand, traffic frequency, time, etc.). We can incorporate the fuzziness into a graph to handle this type of uncertain situation. In this manuscript, we propose the idea of constrained SPP (CSPP) in fuzzy environment. CSPP has an useful real-life application in online cab booking system. The main motivation of this study is to determine a path with minimal cost where traveling time within two locations does not more than predetermined time. We can not predicate the exact time and cost of the path due to uncertain traffic scenarios and another unexpected reasons; still, the geometrical distance between the locations is fixed. Here, we use trapezoidal fuzzy number to describe the edge weight of a fuzzy network/graph for CSPP. We define this CSPP as fuzzy CSPP (FCSPP). The utility of FCSPP is described in several real-life scenarios. We propose a mathematical formulation for the FCSPP and an algorithm is proposed for solving the FCSPP. We describe an application of our proposed algorithm on an online cab booking system.

最短路径问题（SPP）是图论领域中最基本的，众所周知的组合优化问题。在现实生活中，弧在网络/图形的最短路径上称重，具有几个很难精确定义的参数（即容量，成本，需求，流量频率，时间等）。我们可以将模糊性纳入图表中，以处理此类不确定情况。在本文中，我们提出了模糊环境中的约束SPP（CSPP）的想法。CSPP在在线出租车预订系统中具有有用的现实应用程序。这项研究的主要动机是确定一条成本最低的路径，其中两个位置内的旅行时间不超过预定时间。由于不确定的交通场景和其他意外原因，我们无法确定路径的确切时间和成本。位置之间的几何距离仍然是固定的。在这里，我们使用梯形模糊数来描述CSPP的模糊网络/图形的边缘权重。我们将此CSPP定义为模糊CSPP（FCSPP）。在一些实际场景中描述了FCSPP的实用程序。我们为FCSPP提出了数学公式，并提出了解决FCSPP的算法。我们描述了我们提出的算法在在线出租车预订系统上的应用。