Sequence design for Direct-Proportional Length-Based DNA Computing using Population-based Ant Colony Optimization

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. In order to design a set DNA sequences for direct-proportional length-based DNA computing (DPLB-DNAC), a population-based ant colony optimization (P-ACO) method is proposed. Previously, the DNA sequences for DPLB-DNAC are designed using graph method and generate-and-test approach, respectively. The both of methods are without the optimized objective functions process. The proposed method used four objective functions in their process to obtain the best solutions. The results obtained from the proposed method are compared with the sequences generated by graph and generate-and-test methods. The results show that P-ACO approach can generate relatively better DNA sequences in some objectives than others. It can be concluded that proposed algorithm can obtain relatively a better set of DNA sequences for DPLB-DNAC.