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DNA computing and coding have good application prospects in data storage, data computing, data encryption and other fields. Meanwhile, it is very important to design a set of DNA coding set that meets a variety of constraints in today's research. The purpose of DNA coding is to find as many qualified code sets as possible under given conditions or to keep each DNA code in the DNA code set as far as possible from other codes. The former is used in this paper. The algorithm uses the Bloch system to initialize the DNA coding population, and uses the Ant Colony Algorithm to find the optimal DNA coding. At the same time, crossover and mutation operations are added to make the generated population more random and diverse. Experimental results show that the number of code sets obtained by this algorithm under certain specific conditions is better than the number of code sets obtained by other algorithms.

DNA Design Based on Improved Ant Colony Optimization Algorithm With Bloch Sphere