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Following earlier claims that Quantum-inspired Evolutionary Algorithm (QIEA) may offer advantages in high dimensional environments, this paper tests a real-valued QIEA on a series of benchmark functions of varying dimensionality in order to examine its scalability. The results are compared with those from a genetic algorithm using both a binary and real-valued representation. The results show that the QIEA obtains highly competitive results versus the genetic algorithm, while substantially outperforming both versions of the Genetic Algorithm (GA) in terms of running time. This suggests that QIEA may have substantial utility for real-world high dimensional problems.