Levy Equilibrium Optimizer algorithm for the DNA storage code set

Abstract

The generation of massive data puts forward higher requirements for storage technology. DNA storage is a new storage technology which uses biological macromolecule DNA as information carrier. Compared with traditional silicon-based storage, DNA storage has the advantages of large capacity, high density, low energy consumption and high durability. DNA coding is to store data information with as few base sequences as possible without errors. Coding is a key technology in DNA storage, and its results directly affect the performance of storage and the integrity of data reading and writing. In this paper, a Levy Equilibrium Optimizer (LEO) algorithm is proposed to construct a DNA storage code set that satisfies combinatorial constraints. The performance of the proposed algorithm is tested on 13 benchmark functions, and 4 new global optima are obtained. Under the same constraints, the DNA storage code set is constructed. Compared with previous work, the lower bound of DNA storage code set is improved by 4–13%.

Recent Developments in Equilibrium Optimizer Algorithm: Its Variants and Applications

“…The experimental results evidently highlights that the proposed MEO works better than EO and other state-of-the-art metaheuristics, demonstrating its effectiveness in engineering problems. Levy Equilibrium Optimizer (LEO), a new variation of revised EO that incorporates the Levy flight update strategy to improve standard EO, was proposed by Aval et al in the year 2022 [172]. Additionally, the experimental results clearly confirms that the proposed LEO performs better than EO and other contemporary state-of-the-art metaheuristics, including PSO, GWO, GA, GSA, and SSA, demonstrating its effectiveness in DNA storage.…”