BAS在3D路径规划中的应用

说明：  采用改进的遗传算法，对柔性车间调度问题进行求解(Solving flexible shop scheduling problem with improved genetic algorithm)

说明：  在信息素更新上面对于蚁群算法所做出的改进，(In pheromone update, the improvement of ant colony algorithm is made,)

说明：  基于遗传算法的稀步平面阵列，用于平面阵列的稀步优化。可以有效的减少平面阵列的阵元。从而降低阵列天线的成本。(The sparse step linear array based on genetic algorithm is used to optimize the sparse step linear array. It can effectively reduce the array elements of linear array.)

说明：  蜻蜓算法，详细，可运行，对蜻蜓的运动进行描述(Dragonfly algorithm, detailed, operational)

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)

说明：  构建基于改进灰狼优化算法的神经网络数据预测模型(IGWO-BPNN)，目的在于用改进的灰狼优化算法优化神经网络模型，利用神经网络的反向传播优势，改善神经网络算法易于陷入局部最小值的缺陷，提高神经网络模型的预测精度。(The grey wolf algorithm (GWO), which is inspired by the predatory behavior of the gray wolf group, is a new group intelligent optimization algorithm that imitates the leadership of gray wolf population and hunting mechanism in nature)

说明：  包含人群搜索算法源程序，和rastrigin、Schaffer和Spher三个函数的优化，并与PSO比较(Including the source program of crowd search algorithm, and the optimization of rastrigin, Schaffer and Sphere functions, and comparing with PSO)

说明：  爬山改进遗传算法，提供更快的收敛速度，并用于优化极限学习机权值(Mountain climbing improved genetic algorithm to provide faster convergence speed and to optimize the weight of extreme learning machine)

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.)

用matlab实现灰狼优化算法，用于最优化计算(Gray Wolf Optimization Algorithms with MATLAB for Optimal Computing)