Multi-objective and Multi-physics Optimization of Fully Coupled Complex Structures
This work presents an improved approach for multi-objective and multi-physics optimization based on the hierarchical optimization approach of the typical MOCO (“Multi-objective Collaborative Optimization”) whose objective is to solve multi-objective multi-physics optimization problem. In this document, we propose a new hierarchical optimization approach named Improved Multi-objective Collaborative Optimization (IMOCO) whose goal is to decompose the optimization problems of the complex systems hierarchically in two levels (system and disciplinary level) according to the disciplines. In other words, according to the different physical (mechanical-electrical-acoustical) involved in the mechanical structures design. The presented approach uses a NSGA-II “Non-dominated Sorting Genetic Algorithm II” as an optimizer, and uses a coordinator between the system optimizer and the disciplinary optimizer, which has the role, is to ensure consistency between the various disciplines of the complex system. For the purposes of validation of the proposed method, we chose two examples: (i) numerical problem and (ii) engineering problem. These examples are solved using the proposed IMOCO method and the previous approaches. The obtained results are compared well with those obtained from the previous approaches: (i) non-hierarchically based AAO optimization approach and (ii) hierarchically based MOCO optimization approach, which show the good performance of our proposed IMOCO method.
KeywordsAuxiliary Variable Coordination Problem Mechanical Optimizer Coupling Variable Collaborative Optimization
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