智能优化算法作为新兴的搜索算法，一般是指利用自然界的生物系统与优化过程的某些相似性而逐步发展起来的优化算法，如遗传算法、粒子群算法、蚁群算法等，它们通过对搜索空间中的一组解按概率规则操作得到下一组解。

人工鱼群算法源于对鱼群运动行为的研究，是一种新型的智能仿生优化算法。它具有较强的鲁棒性、优良的分布式计算机制、易于和其它方法结合等优点。目前对该算法的研究、应用已经渗透到多个应用领域，并由解决一维静态优化问题发展到解决多维动态组合优化问题。

-As an emerging intelligent optimization algorithms search algorithm, generally refers to the use of natural biological systems and the optimization process some similarities and gradually developed optimization algorithms, such as genetic algorithms, particle swarm optimization, ant colony algorithm, which searches through space of solutions according to the probability of a rule action to get the next set of solutions. AFSA stems from the behavior of fish movement, is a new type of intelligent bionic optimization algorithm. It has strong robustness, excellent distributed computer system, easy to combine with other methods, etc.. At present the algorithm research, application has penetrated into multiple applications, by solving one-dimensional static optimization problem developed to solve multidimensional dynamic combinatorial optimization problems.