用于求解约束优化问题的算法，算法为差分进化/遗传算法/微粒群算法的融合。对于“[7] T. P. Runarsson and X. Yao, Stochastic ranking for constrained evolutionary optimization, IEEE Trans. Evol. Comput., vol. 4, no. 3, pp. 284-294, Sep. 2000”中给出的13个标准测试函数，均能得到问题最优解。如有任何疑问，请于http://2shi.phphube

介绍带随机排序策略的进化策略算法。该算法是姚新老师的经典文章，文章中重点介绍了随机排序策略，及其优点，值得好好学习。-Stochastic Ranking for Constrained Evolutionary Optimization

利用狮蚁群算法实现火电机组功能调度，参数处理使用stochastic ranking(Performance scheduling of thermal power generating units is based on the lion ant colony algorithm. Parametric processing is stochastic)

借用MFO算法实现对于火电机组调度问题的优化，在处理约束变量时使用了stochastic ranking的方法(The MFO algorithm is adopted to optimize the scheduling problems of thermal power units. When dealing with constraint variables, the stochastic ranking method is adopted)