# An Intelligent Optimization Algorithm for Constructing a DNA Storage Code: NOL-HHO
###### Abstract  
The high density, large capacity, and long-term stability of DNA molecules make them an emerging storage medium that is especially suitable for the long-term storage of large datasets. The DNA sequences used in storage need to consider relevant constraints to avoid nonspecific hybridization reactions, such as the No-runlength constraint, GC-content, and the Hamming distance. In this work, a new nonlinear control parameter strategy and a random opposition-based learning strategy were used to improve the Harris hawks optimization algorithm (for the improved algorithm NOL-HHO) in order to prevent it from falling into local optima. Experimental testing was performed on 23 widely used benchmark functions, and the proposed algorithm was used to obtain better coding lower bounds for DNA storage. The results show that our algorithm can better maintain a smooth transition between exploration and exploitation and has stronger global exploration capabilities as compared with other algorithms. At the same time, the improvement of the lower bound directly affects the storage capacity and code rate, which promotes the further development of DNA storage technology. DNA storage; DNA coding design; HHO algorithm; OBL addressref=aff1]J.-M.  
digital information into \"A\", \"T\", \"C\" or \"G\" sequences using a pre-developed coding scheme, and then synthesizing these sequences into oligonucleotides or long DNA fragments. The process of sequencing is the opposite of this. However, the quality of the coding sequence in the synthesis process directly affects the efficiency of these reactions and the success of decoding, so it is necessary to construct a robust coding sequence. In response to this, our predecessors have done a lot of work on DNA storage. [PERSON] (1988) first proposed to construct a DNA storage model, which could be used to construct DNA memory with a large storage capacity, thus laying the foundation for DNA storage technology research. This subfield has continued to grow slowly over the past few years. [PERSON] et al. [PERSON] et al. (2018) further developed a DNA-based double steganographic technique for encoding secret messages in DNA. An additional paper [PERSON] et al. (2018) gave three important reasons for why DNA molecules are an ideal media for long-term information storage. Other authors [PERSON] (2018) described a memory model made of DNA, called Nested Primer Molecular Memory (NPMM), and proved its feasibility through experiments. [PERSON] et al. [PERSON] et al. (2018) described an improved Huffman coding method for information storage using DNA, and their experiments showed that this method was suitable for automatic information retrieval. Additionally, [PERSON] et al. [PERSON] et al. (2018) wrote 5.27 Mb bits of files into DNA microchips and successfully used DNA sequencing to decode these files, which was an important milestone in storage history. After this, storage research using DNA has entered an era of rapid development. [PERSON] et al. [PERSON] et al. (2018) used a three-element Huffman-encoded synthetic DNA sequence on 739K different format files and achieved a sequencing accuracy of 100%. [PERSON] et al. [PERSON] et al. (2018) described the first DNA storage architecture that allowed random access to blocks of data and the rewriting of information. This innovation ensured the reliability of the data while increasing the data storage capacity. Later, [PERSON] et al. proposed an archival storage system-based architecture and a new coding scheme, which provided random access and controllable redundancy for DNA storage B. (2018). [PERSON] et al. [PERSON] et al. (2018) developed an efficient and robust forward error correction scheme for DNA channels, and this solution could deal with insertions, deletions, and swap errors. A lot of work-related to DNA storage has appeared in the literature over the past three years, which shows its practical value. For example, [PERSON] et al.