This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is ...This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.展开更多
Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development o...Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development of process planning methods that take energy consumption into account.An energy-efficient process planning model that incorporates manufacturing time and energy consumption is proposed.For solving the problem,an improved genetic algorithm method is employed to explore the optimal solution.Finally,a case study for process planning is given.The experimental result generates interesting effort,and therefore allows improving the energy efficiency of manufacturing processes in process planning.展开更多
针对弹药装配结构复杂、零件数量多和装配效率低等问题,提出一种基于模型定义(model based definition,MBD)的弹药装配序列规划生成方法。在定义装配序列可行性的基础上,构建装配规划的适应度函数,提出包含精英种群的基于改进遗传算法(g...针对弹药装配结构复杂、零件数量多和装配效率低等问题,提出一种基于模型定义(model based definition,MBD)的弹药装配序列规划生成方法。在定义装配序列可行性的基础上,构建装配规划的适应度函数,提出包含精英种群的基于改进遗传算法(genetic algorithm,GA)的装配序列规划算法。基于UG/NX二次开发技术,设计和开发MBD的装配序列规划系统。以某引信子装配体为例进行应用验证的结果表明,所提方法有效且稳定。展开更多
The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network st...The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm展开更多
基金funded by the Joint Funds of the National Natural Science Foundation of China (61079001)
文摘This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.
基金supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme(No.294931)the National Science Foundation of China (No.51175262)+1 种基金Jiangsu Province Science Foundation for Excellent Youths(No.BK2012032)Jiangsu Province Industry-Academy-Research Grant(No.BY201220116)
文摘Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development of process planning methods that take energy consumption into account.An energy-efficient process planning model that incorporates manufacturing time and energy consumption is proposed.For solving the problem,an improved genetic algorithm method is employed to explore the optimal solution.Finally,a case study for process planning is given.The experimental result generates interesting effort,and therefore allows improving the energy efficiency of manufacturing processes in process planning.
文摘针对弹药装配结构复杂、零件数量多和装配效率低等问题,提出一种基于模型定义(model based definition,MBD)的弹药装配序列规划生成方法。在定义装配序列可行性的基础上,构建装配规划的适应度函数,提出包含精英种群的基于改进遗传算法(genetic algorithm,GA)的装配序列规划算法。基于UG/NX二次开发技术,设计和开发MBD的装配序列规划系统。以某引信子装配体为例进行应用验证的结果表明,所提方法有效且稳定。
文摘The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm
