A rapid approach based on empirical formulas and graph traversal algorithms to automatic generation of fragrance formulas

This article proposes a novel approach for improving the efficiency of fragrance designing and the accuracy of automatic fragrance formula creation based on empirical fragrance formulas and graph traversal algorithms. By effectively extracting the composition information and further analyzing the combination of fragrance materials in 210 fragrance formulas, a relational network model was constructed in the form of a graph to illustrate the relationship between the ingredients used in the formulas. Additionally, a fragrance ingredients information database of 344 common ingredients was constructed and used as a reference for perfumers when setting algorithmic constraints based on their experience. Finally, an automatic fragrance formula creation algorithm was established by constructing a relational network subgraph and finding fragrance formula solutions with the help of depth-first search algorithm that satisfies the constraint conditions and combining with appropriate statistical strategy that could determine the usage of each component in the new fragrance formula. By testing the algorithm with the goal of creating a floral fragrance, the resulting formula well fulfilled our expectations and had practical application value.