Due to the increasing scarcity of precious woods and the severe environmental issues caused by overexploitation, it is necessary to mimic the appearance of precious woods by dyeing ordinary wood. Computer-assisted dyeing technology was utilized to achieve high-precision dyeing of ordinary wood, thus creating substitutes that resemble precious woods and reducing dependence on them. Initially, based on the concept of gene expression programming (GEP), a multi-expression programming (MEP) algorithm was proposed to predict dye ratios. Considering the complex interactions among various dyes, multi-gene expression was employed. The MEP algorithm can handle these complex interactions between multiple dyes, resulting in more intuitive functional expressions. To enhance the function mining accuracy of MEP, the probabilities of mutation and recombination operators ware adaptively adjusted, and parallel programming was employed to boost function mining efficiency. Compared to gene expression programming results, MEP delves deeper into functional relationships and achieves a relative deviation of 0.113 in color prediction.