提出一种采用贝叶斯网络表示概率模型的多目标分布估计算法(multi-objective estimation of distribution algo-rithm,MEDA)。通过构建这样的网络模型,对模型进行抽样生成新个体,再对新个体进行变异操作,以增加种群的多样性,提高算法的...提出一种采用贝叶斯网络表示概率模型的多目标分布估计算法(multi-objective estimation of distribution algo-rithm,MEDA)。通过构建这样的网络模型,对模型进行抽样生成新个体,再对新个体进行变异操作,以增加种群的多样性,提高算法的搜索能力。这种生成个体的方法结合非劣分层以及截断选择机制,可以获得很好地逼近多目标问题的Pareto前沿且分布均匀的非劣解集。用MEDA对某高空长航时无人机机翼结构进行多目标优化设计,找到高质量的非劣解集,为设计者作决策提供很好的参考依据。根据所得到的非劣解集,设计者可以很好地进行权衡折衷,找出最符合要求的设计方案。同时,还可以了解各目标之间的变化关系,定量化了解一个目标的改进将导致其余目标恶化的程度。研究表明,多目标分布估计算法可以有效求解复杂结构的优化设计问题。展开更多
Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance un...Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle（UAV）. In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained.展开更多
文摘提出一种采用贝叶斯网络表示概率模型的多目标分布估计算法(multi-objective estimation of distribution algo-rithm,MEDA)。通过构建这样的网络模型,对模型进行抽样生成新个体,再对新个体进行变异操作,以增加种群的多样性,提高算法的搜索能力。这种生成个体的方法结合非劣分层以及截断选择机制,可以获得很好地逼近多目标问题的Pareto前沿且分布均匀的非劣解集。用MEDA对某高空长航时无人机机翼结构进行多目标优化设计,找到高质量的非劣解集,为设计者作决策提供很好的参考依据。根据所得到的非劣解集,设计者可以很好地进行权衡折衷,找出最符合要求的设计方案。同时,还可以了解各目标之间的变化关系,定量化了解一个目标的改进将导致其余目标恶化的程度。研究表明,多目标分布估计算法可以有效求解复杂结构的优化设计问题。
文摘Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle（UAV）. In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained.
