Solving neutrosophic critical path problem using Python

Abstract

The study observation offers a method for project control known as the Neutrosophic Critical Path Method (NCPM) which combines the traditional Critical Path Method (CPM) with neutrosophic sets. Dealing with actual global situations that frequently pose demanding situations for CPM specifically while initiatives involve interconnected operations. The presence of uncertainties creates hurdles during challenge execution, due to incomplete and uncertain data. By illustrating surroundings for instance this research outlines the transition from CPM to NCPM and highlights its advantages. Numerical examples have been implemented for solving NCPM, that discover solutions in the face of uncertainty. Furthermore, the advanced Python software specifically designed for network evaluation permits willpower of critical route lengths. This synthesis complements selection-making in project control that paves the manner for precise management of complicated situations.