Enhancing Critical Path Problem in Neutrosophic Environment Using Python']Python

In the real world, one of the most common problems in project management is the unpredictability of resources and timelines. An efficient way to resolve uncertainty problems and overcome such obstacles is through an extended fuzzy approach, often known as neutrosophic logic. Our rigorous proposed model has led to the creation of an advanced technique for computing the triangular single-valued neutrosophic number. This innovative approach evaluates the inherent uncertainty in project durations of the planning phase, which enhances the potential significance of the decision-making process in the project. Our proposed method, for the first time in the neutrosophic set literature, not only solves existing problems but also introduces a new set of problems not yet explored in previous research. A comparative study using Python programming was conducted to examine the effectiveness of responsive and adaptive planning, as well as their differences from other existing models such as the classical critical path problem and the fuzzy critical path problem. The study highlights the use of neutrosophic logic in handling complex projects by illustrating an innovative dynamic programming framework that is robust and flexible, according to the derived results, and sets the stage for future discussions on its scalability and application across different industries.