This study examines the utility of meta-grammar constant generation on a series of benchmark problems. The performance of the meta-grammar approach is compared to a grammar which incorporates grammatical ephemeral random constants, digit concatenation, and an expression based approach. It is found that the meta-grammar approach to constant creation is particularly beneficial on the dynamic problem instances in terms of the best fitness values achieved. Categories and Subject Descriptors I.2.0 [Computing Methodologies]: Artificial Intelligence— General General Terms Algorithms, Theory Keywords Constant Creation, Digit Concatenation, Ephemeral Random Constants, Genetic Programming, Grammatical Evolution, meta-Grammars