Simple genetic algorithm started by orthogonal design of experiments

Genetic algorithm using orthogonal design of experiments as the initial population is proposed and evaluated. It improves performance in low variable interaction problems. However, the efficiency is not well recognized in benchmarks of high interactions. The performance of the random initialized and the OD-initialized simple genetic algorithm depend on the problem and the size.