多星测控调度的遗传算法分析

针对多星过站冲突问题,以工程需求为导引,建立了多星测控调度模型,并采用遗传算法对其进行求解.从全局和局部搜索两种策略入手,以可用可见弧段为对象,设计了"全弧段"编码和基于协同进化的编码两种编码方式,给出了对应算法的实现流程和遗传操作算子,对两种编码方式的求解效率进行了分析.通过仿真对两种编码的求解质量与时间开销性能作了验证,由此得出了两种编码和对应搜索策略的适用范围.据此开发的系统已成功应用于航天顶层设计的辅助决策.     

多UCAV协同航路规划算法

针对多UCAV协同航路规划问题,将协同进化理论与扩展Voronoi图模型相结合,提出了一种基于扩展Voronoi图模型与协同进化算法的多UCAV协同航路规划方法。该方法通过协同进化理论的合作机制实现了规划航路的空域协同,通过采用层次分解策略实现了规划航路的时域协同,并且对染色体设计、个体适应度以及进化操作等关键问题进行了研究。     

Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm(MPEA) framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution(CC) algorithm combined with non-dominated sorting genetic algorithm II(NSGA-II) is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multiobjective genetic algorithm(MOGA), multi-objective evolutionary algorithm based on decomposition(MOEA/D), CC-based multi-objective algorithm(CCMA) as well as other two MPEAs with different migration interval strategies.     

企业协同进化的生态机制及其对策研究

企业的进化与生物的进化相类似，但也有区别。在企业与其环境构成的企业生态系统中，一个企业的进化可以影响到其他企业的进化，反过来，其他企业的进化又影响到该企业的进化路径，最终导致整个系统成为一个互相作用、相互促进的整体。企业协同进化的生态特点是不对称性、方向性、适应性、进步性、不可逆性、扩展性。企业协同进化的生态学对策是：（1）正确看待竞争压力；（2）适应环境变化；（3）创建学习型组织；（4）共同进化。