Double Orthogonal Arrays Based Genetic Algorithm for Primer Design

In this paper, a double orthogonal array based genetic algorithm is proposed to decrease the searching space and increase the feasible quality of primers. The key point of the proposed algorithm is to achieve the elitism goal by applying the orthogonal arrays (OAs) that is used in quality engineering with a small amount of experimental features. The result shows that the proposed algorithm converges faster than the traditional GA. Based on the design properties such as unique, GC content, melting temperature, temperature difference and annealing, the proposed algorithm can derive the solutions more precisely and efficiently. The primer pairs obtained can exactly match to the PCR traits.