A binary vector evaluated particle swarm optimization based method for DNA sequence design problem

Deoxyribonucleic Acid (DNA) has certain unique properties such as self-assembly and self-complementary in hybridization, which are important in many DNA-based technologies. Hybridization of DNA can be controlled by properly designing DNA sequences. In this study, sequences are designed such that each sequence uniquely hybridizes to its complementary sequence, but not to any other sequences. Vector evaluated particle swarm optimization (VEPSO) is employed to solve the DNA sequence design problem by minimizing four objective functions, namely similarity, H
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, continuity, and hairpin, subjected to two constraints: melting temperature and GC
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. Non-dominated solutions can be produced, which are better than other research works where only a set of sequences is generated.