Multi-Objective Collaborative Optimization Based on Evolutionary Algorithms

作者：Su Ruiyi^*; Gui Liangjin; Fan Zijie

来源：Journal of Mechanical Design, 2011, 133(10): 104502.

DOI：10.1115/1.4004970

• multidisciplinary design optimization
• multi-objective optimization
• collaborative optimization

This paper proposes a novel multi-objective collaborative optimization (MOCO) approach based on multi-objective evolutionary algorithms for complex systems with multiple disciplines and objectives, especially for those systems in which most of the disciplinary variables are shared. The shared variables will conflict when the disciplinary optimizers are implemented concurrently. In order to avoid the confliction, the shared variables are treated as fixed parameters at the discipline level in most of the MOCO approaches. But in this paper, a coordinator is introduced to handle the confliction, which allocates more design freedom and independence to the disciplinary optimizers. A numerical example is solved, and the results are discussed. [DOI: 10.1115/1.4004970]

• 出版日期2011-10
• 单位清华大学