GA

说明：  经典遗传算法案例，利用遗传算法求解铁罐问题(genetic algorithm optimization)

改进的灰狼算法用于重油热解模型的建模程序(greywolf algorithm for observation of heavy oil thermal cracking)

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：  原始的最优化算法，用来求解最小值最大值，适合新手入门学习(fruit fly optimization)

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：  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)

说明：  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)

采用蚁群算法对BP神经网络进行优化，并结合实例进行应用验证。(The ant colony algorithm is used to optimize the BP neural network, and an example is used to validate it.)

在蚁群算法的基础上进行改进，使优化效果更加明显(On the basis of ant colony algorithm, the optimization effect is more obvious.)

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)