多目标优化进化算法目前公认效果收敛性最好的算法NSGA2c++源码,具有一般性，可在此基础上继续改进，对实现其他多目标优化算法很有帮助.-Multi-objective optimization evolutionary algorithm is currently the best recognized effect of convergence of the algorithm NSGA2c++ Source, with the general, could be on this basis

多宇宙并行量子多目标进化算法。该算法主要思想如下：将所有的量子个体按给定的拓扑结构分成多个独立的子种群，划分为多个宇宙；采用目标个体均匀分配原则和动态调整旋转角机制对各宇宙量子个体进行演化；宇宙之间采用最佳移民操作来交换信息，设计最优个体保留方案以便各宇宙共享全局信息，提高算法的执行效率。-Multi-quantum universe parallel multi-objective evolutionary algorithm. The main idea of ​ ​ t

IEEE 30 BUS SYSTEM Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The generation of Unit Commitment solution is guaranteed by DEEPSO, which is a hybrid DE-EA-PSO algorithm, where DE stands for Differential

Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The generation of Unit Commitment solution is guaranteed by DEEPSO, which is a hybrid DE-EA-PSO algorithm, where DE stands for Differential Evolution, EA for