Solving neutrosophic minimal cost flow problem using multi-objective linear programming problem

The Linear Programming (LP) model, renowned for its robust modeling capabilities, is a highly effective tool for solving real-world problems and optimizing tasks with specific objective. A key component of the LP model is the Minimum Cost Flow (MCF), which aims to minimize the transportation cost of a single product through a capacitated network. This article focuses on the MCF problem with neutrosophic arc cost, a scenario that often arises in real-world situations due to the complexity and uncertainty of data. The neutrosophic theory plays a crucial role in handling this vagueness. The primary objective of this paper is to find the optimal solution to the neutrosophic MCF problem using SVTN numbers.