It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optima...It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optimal combination under various constraints not only involves numerical calculations but also is an NP-hard combinatorial problem.To solve the problem,an adaptive genetic algorithm based on cluster search,which is divided into two phases,is put forward.In the first phase,according to the density,all individuals can be homogeneously scattered over the whole solution space through crossover and mutation and better individuals are collected as candidate cluster centres.In the second phase,the search is confined to the neighbourhood of some selected possible solutions to accurately solve with cluster radius decreasing slowly,meanwhile all clusters continuously move to better regions until all the peaks in the question space is searched.This algorithm can efficiently solve the combination problem.Taking the optimization on decision-making of aircraft maintenance by the algorithm for an example,maintenance which combines multiple parts or tasks can significantly enhance economic benefit when the halt cost is rather high.展开更多
三维无人机路径规划问题旨在满足安全性条件的前提下为无人机规划出一条最佳的飞行路径.本文通过数学建模的方式构建出无人机路径规划的成本函数,从而无人机路径规划问题转化为多约束的优化问题,并使用元启发式算法来求解该问题.针对人...三维无人机路径规划问题旨在满足安全性条件的前提下为无人机规划出一条最佳的飞行路径.本文通过数学建模的方式构建出无人机路径规划的成本函数,从而无人机路径规划问题转化为多约束的优化问题,并使用元启发式算法来求解该问题.针对人工兔优化算法收敛慢以及易陷入局部最优的缺陷,本文开发了一种基于Levy飞行、自适应柯西变异以及精英群遗传策略改进的人工兔优化算法(Artificial Rabbit Optimization algorithm based on Levy flight,adaptive Cauchy mutation,and elite population Genetic strategy,LCGARO).将LCGARO与6个经典和先进的元启发式算法在29个CEC2017测试函数和6个复杂度不同的三维无人机路径规划地形场景中进行多方面对比实验.对比实验结果证明,在CEC2017测试函数的对比实验中,本文提出的LCGARO算法在22个测试函数中具有更优的寻优精度.在无人机路径规划实验中,LCGARO算法在5个地形场景中能够规划出总成本函数值最小的飞行路径.展开更多
基金supported by the National Natural Science Foundation of China(6107901361079014+4 种基金61403198)the National Natural Science Funds and Civil Aviaiton Mutual Funds(U1533128U1233114)the Programs of Natural Science Foundation of China and China Civil Aviation Joint Fund(60939003)the Natural Science Foundation of Jiangsu Province in China(BK2011737)
文摘It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optimal combination under various constraints not only involves numerical calculations but also is an NP-hard combinatorial problem.To solve the problem,an adaptive genetic algorithm based on cluster search,which is divided into two phases,is put forward.In the first phase,according to the density,all individuals can be homogeneously scattered over the whole solution space through crossover and mutation and better individuals are collected as candidate cluster centres.In the second phase,the search is confined to the neighbourhood of some selected possible solutions to accurately solve with cluster radius decreasing slowly,meanwhile all clusters continuously move to better regions until all the peaks in the question space is searched.This algorithm can efficiently solve the combination problem.Taking the optimization on decision-making of aircraft maintenance by the algorithm for an example,maintenance which combines multiple parts or tasks can significantly enhance economic benefit when the halt cost is rather high.
文摘三维无人机路径规划问题旨在满足安全性条件的前提下为无人机规划出一条最佳的飞行路径.本文通过数学建模的方式构建出无人机路径规划的成本函数,从而无人机路径规划问题转化为多约束的优化问题,并使用元启发式算法来求解该问题.针对人工兔优化算法收敛慢以及易陷入局部最优的缺陷,本文开发了一种基于Levy飞行、自适应柯西变异以及精英群遗传策略改进的人工兔优化算法(Artificial Rabbit Optimization algorithm based on Levy flight,adaptive Cauchy mutation,and elite population Genetic strategy,LCGARO).将LCGARO与6个经典和先进的元启发式算法在29个CEC2017测试函数和6个复杂度不同的三维无人机路径规划地形场景中进行多方面对比实验.对比实验结果证明,在CEC2017测试函数的对比实验中,本文提出的LCGARO算法在22个测试函数中具有更优的寻优精度.在无人机路径规划实验中,LCGARO算法在5个地形场景中能够规划出总成本函数值最小的飞行路径.
