蚁群算法求解TSP问题程序

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：  基于精英变异算法的电动汽车充电优化策略以及结果的可视化(EV charging optimization strategy based on elite mutation algorithm and the visualization of results)

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：  用matlab实现levy概率分布，并作图，用于进化算法中调整步长(Using MATLAB to realize levy probability distribution and make a map for adjusting step size in evolutionary algorithm)

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)

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：  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)

基于子区域的粒子群优化算法研究，粒子群算法是进化算法的一种，多用于路径规划等问题(Subregion-based Particle Swarm Optimization)

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.)

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)