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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.