Combinatorial splitting methods help visualise complicated arrangements in n-dimensional discrete structures. Using the Riemann hypothesis related with broad variety principle to combinatorial splitting methods may improve them, this paper shows. The paper presents a single Riemann speculation-based department process improvement. This will improve assessment and control of large-scale combinatorial problems. A novel approach that enhances the quality of responses for high-dimensional discrete structures, simplifies computations, and improves existing methods is based on the Riemann hypothesis. Many trials were done to compare this new strategy to prior department tactics. Results show that dividing tasks is now greener, particularly for difficult combinatorial combinations. This work combines number theory and combinatory to solve discrete mathematics problems in unique ways.