In this paper, a hybrid particle swarm optimization algorithm (HPSO) is proposed for the DNA fragment assembly (DFA) problem by maximizing the overlapping-score measurement. The smallest position value (SPV) rule is used for encoding the particles to enable PSO to be suitable for DFA, and the Tabu search algorithms are used to initialize the particles. Additionally, a simulated annealing (SA) algorithm-based local search is utilized for local search to improve the best solution after the PSO search process. Finally, the results show that HPSO can significantly get better overlap score than other PSO-based algorithms with different-sized benchmarks.
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