An Improved Collaborative Optimization Based onMultidisciplinary Inconsistency
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摘要:
分析了MDO(Multidisciplinary Design Optimization)中广泛应用的协同优化算法的特点和存在的问题,提出了一种基于学科间差异信息的协同优化改进算法COMI(Collaborative Optimization based on Multidisciplinary Inconsistency)。利用学科间差异信息构造了系统级松弛约束和系统级罚函数,利用遗传算法作为系统级优化算法,并采用标准算例比较了标准CO(Collaborative Optimization)算法、松弛CO算法与COMI算法的性能。结果表明COMI算法在设计结果可行性和最优值上平衡性较好。
Abstract:
Reasons that cause computational difficulties in collaborative optimization are analyzed and the COMI(Collaborative Optimization Based on Multidisciplinary Inconsistency) algorithm is presented.Relax constraints and system level penalty function are constructed based on inconsistency information between disciplinaries, and a GA optimizer is used to solve a typical MDO question.Simulation results show that the feasibility and the optimal value of COMI is more balanced than the standard CO algorithm and the relax CO algorithm.
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冯向军,戴金海.基于学科间差异信息的协同优化改进算法. An Improved Collaborative Optimization Based onMultidisciplinary Inconsistency[J].国防科技大学学报,2008,30(2):128-134.