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说明：  NSGA-III evolutionary algorithm using MATLAB

解决车间资源分配的动态调度问题，采用遗传算法(Solving the dynamic scheduling problem of workshop resource allocation, using genetic algorithm)

标准萤火虫算法,程序运行稳定，可以自测！！！！！！！(Standard firefly algorithm, the program runs stably and can be self-tested! ! ! ! ! ! !)

说明：  对于蚁群算法做出的改进，按信息素大小进行排序(For the improvement of ant colony algorithm, it is sorted by pheromone size)

灰狼算法和粒子群算法的结合，是两种种群算法的结合，值得一看(The combination of grey Wolf algorithm and particle swarm optimization is a combination of two population algorithms, which is worth a look)

天牛须算法的简单编写，需要自己替换适应度函数(The algorithm is simple and needs to replace its fitness function.)

说明：  哈里斯鹰算法HHO的一个java版本 ， 作者来自 Dr. Oguz Emrah Turgut(Dr. Oguz Emrah Turgut comes from Department of Mechanical Engineering, Faculty of Engineering, Ege University, 35100 Bornova, Izmir, Turkey)

一个实现多目标进化计算的数据集，用来测试不同的真实pareto前沿(A data set for multi-objective evolutionary computation to test different real Pareto Frontiers)

说明：  利用遗传算法求解柔性车间调度问题，采用Python编程实现(Using Genetic Algorithm to Solve Flexible Workshop Scheduling Problem)

这是MATLAB中最新的优化工具箱，它利用最近提出的7种算法来优化您的问题。 此工具箱中提供的算法包括： 灰狼优化器（GWO），蚂蚁狮子优化器（ALO），多功能优化器（MVO），蜻蜓算法（DA），蛾火焰算法（MFO），正弦余弦算法（SCA）和鲸鱼优化算法（WOA） 。(This is the latest optimization toolbox in MATLAB, which optimizes your problem using seven algorithms recently proposed. The algorithms provided in this toolbox include: GWO, ALO, MVO, DA, MFO, SCA and WOA.)