Improved Particle Swarm Based on Elastic Collision for DNA Coding Optimization Design

In DNA computing, the design of DNA coding sequences is an important factor affecting the reliability of DNA computing. In different DNA sequence designs, suitable constraints should be selected and the sequence design should be rationalized according to these constraints. In this paper, an improved particle swarm optimization algorithm based on elastic collision strategy (EC-PSO) is used to optimize the design of DNA sequences by using an adaptation function that satisfies multiple constraints. EC-PSO uses the idea of elastic collision to improve the optimal and worst positions within the population, introduces the flight means of the sparrow search algorithm (SSA) to enhance the search capability of the algorithm and increase the diversity of the population; then introduces the harmony search algorithm to the population is then fine-tuned to improve the quality of the solution. The effectiveness of the algorithm was verified by comparing it with the other six algorithms in eight test functions. Finally, the sequence designed was more reasonable in the DNA optimal design experiment.