《智能优化方法》汪定伟

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：  粒子群算法的寻优机制，另附十余个测试函数。主程序为test_basic(Particle Optimization Algorithm)

基于CEC——2017benchmark测试集，计算最优 修正的果蝇算法，弥补原始果蝇算法在负数集上的缺失(modify fruit fly optimization)

说明：  差分进化原始算法，有多个案例用于理解和运用(The original differential evolution algorithm has many cases for understanding and application)

说明：  蚁群算法求解TSP问题程序,代码简单明了，易于理解。(Ant colony algorithm for TSP)

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)

说明：  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.)

根据Degree Centrality、Co-Expression Weighted by clustering Coefficient、Betweenness Centrality、PeC等六种参数的计算来寻找关键蛋白质(Find the key proteins according to the calculation of Degree Centrality, Co-Expression Weighted by clustering Coefficient, Betweenness Centrality, PeC and other six parameters.)

说明：  一种改进的差分算法，包含cec2005部分单目标无约束测试函数(An improved difference algorithm)

说明：  多目标遗传算法的完整代码，测试函数使用ZDT和DTLZ函数(Complete code of multi-objective genetic algorithm, test function uses ZDT and dtlz function)