DNA sequence design for direct-proportional length-based DNA computing: particle swarm optimization vs population based ant colony optimization

Abstract

Generally, in DNA computing, the DNA sequences used for the computation should be critically designed in order to reduce error that could occur during computation. Previously, direct-proportional length-based DNA computing which involved DNA sequences with different lengths has been implemented to solve the shortest path problem. In this study, particle swarm optimization (PSO) and population-based ant colony optimization (P-ACO) are employed to design DNA sequences with different lengths and the results obtained are compared. Further comparison with the sequences generated by graph and generate-and-test methods is presented. The results show that P-ACO approach can generate relatively better DNA sequences in some objectives than PSO approach and the other methods. It can be concluded that the P-ACO algorithm can obtain relatively a better set of DNA sequences for DNA computing with length constraints.