Design Of DNA Coding Set Based On Hybrid Ant Colony Algorithm

Computer technology is known as one of the three scientific revolutions of the 20 th century.With the progress of technology,electronic computers play an important role in all aspects of human society.However,with the development of society,human beings produce more and more data every day,which makes the use of traditional electronic computers spend more and more time,and people have to find new alternatives,DNA computing is a powerful exploration of human beings in the field of computing.DNA computing is a new computing model with biomolecular DNA as computing medium and biochemical reaction as computing tool.DNA coding is a branch of DNA computing,and it also has many problems: first,it directly affects the synthetic quality of DNA sequence.Secondly,the quality of coding directly affects the hybridization reaction according to the original plan.Finally,the quality of coding directly affects the number of coding and the expansion of solution space.Therefore,based on the above situation,we can expand two directions of DNA coding: DNA coding optimization and DNA coding set design.DNA coding optimization refers to selecting the optimal DNA coding from the DNA coding set that meets the constraints? The set design of DNA coding refers to obtaining as many DNA codes that meet the constraints as possible within the specified coding length.At present,the commonly used DNA coding constraints include combinatorial constraints and thermodynamic constraints.These combinatorial constraints can ensure that the obtained DNA coding does not cross to a certain extent,and then obtain high-quality coding.The research direction of this paper is the set design of DNA coding,and the work done is as follows:(1)A hybrid ant colony algorithm combining ant colony algorithm and improved random search(AOC IRS)algorithm is proposed,and the algorithm is applied to DNA coding design.Based on the shortcomings and deficiencies of traditional random search algorithms,an improved random search algorithm is proposed,which can effectively solve the problem of insufficient solution space.The hybrid algorithm first uses random initialization to obtain the initial population,and then uses the ant colony algorithm to obtain the best one(or several)high-quality codes.At the same time,genetic algorithm is added to avoid the ant colony algorithm from falling into the local optimum as much as possible.In the case of,the ability to search the local solution space is improved,and finally the improved version of the random search algorithm is used to further expand the solution space.Experiments show that the hybrid algorithm can obtain better results than the previous ones.(2)According to Bloch sphere coding(BSC),an improved ant colony hybrid algorithm based on Bloch sphere coding is proposed and applied to DNA coding design.The algorithm uses Bloch Sphere coding for initialization.Compared with the traditional random initialization method,this initialization enables the group to obtain better diversity,thereby increasing the possibility of obtaining high-quality coding? at the same time,it is carried out on the basis of the ant colony algorithm.Improved,and proposed an improved version of the ant colony algorithm.Compared with the traditional ant colony algorithm,this algorithm reduces the calculation time of the algorithm,reduces the calculation time of the improved version of the ant colony algorithm,and improves the efficiency of the code? use this article The results obtained by the algorithm are compared with those of the predecessors.Some of the results are consistent with the results of the predecessors,and some are better than those of the predecessors,indicating the feasibility of the algorithm.Through the above two experimental results,we can know that the hybrid ant colony algorithm can expand better solution space and more coding sets,which provides a useful reference for the follow-up research of DNA coding.