A DNA Coding Design based on Multi-objective Evolutionary Algorithm with Constraint

Abstract

Due to the excessive number of objective functions in DNA coding problem, there are dominant impedance between solutions which makes it difficult to evaluate the solutions and the algorithm is hard to converge. And traditional multi-objective evolutionary algorithms tend to fall into premature convergence when dealing with DNA coding problems. We proposed an Improved Nondominated Sorting Genetic Algorithm II with Constraint (ICNSAG-II) to deal with these problem. Firstly, the DNA coding problem and its 6 coding constraints are introduced. Secondly, the constraint function and Block operator are used to reduce the dimensionality of the DNA coding problem, so that the objective function is reduced to two, which make it easy to optimize using multi-objective evolutionary algorithms. Finally, by comparing with the sequences generated by the comparative algorithm, it was verified that the DNA sequences generated by ICNSGA-II have good chemical stability and are able to prevent the of unexpected secondary structures and non-specific hybridization reactions.