求解MSA问题的新型遗传算法

为了克服传统遗传算法求解MSA问题速度慢的缺点，提出了一种新型自适应遗传算法，不使用交叉算子，只使用变异和选择算子，提出了在算法初始化时引入种子的策略，用星比对算法生成一个种子，保证了解的质量，使用灾变算子来确保算法的搜索能力，该算法模拟了自然界进化的周期性，较好地解决了群体多样性和收敛深度的矛盾。

New genetic algorithm of MSA solution problem

Multiple sequence alignment (MSA) is a typical NP problem,in order to solve this time-comsuming problem which genetic algorithm will encounter in multiple sequence alignment,a new adaptive genetic algorithm was presented.The algorithm employed only mutation operator and selection operator to produce the offspring,instead of crossover operator.Further,seed strategy used in the procedure of initialization ensured the quality of result,and the seed was produced by star alignment algorithm.In addition,a specific cataclysm operator was designed to ensure its searching capability.The algorithm simulates the recurrence of nature evolution process was simulated with this algorithm,and the contradiction among the diversity of population and the convergence speed were solved.