An integrated method of multi-objective optimization for complex mechanical structure
An integrated method of multi-objective optimization for complex mechanical structures is presented, which integrates prototype modeling, FEM analysis and optimization. To explore its advantages over traditional methods, optimization of a manipulator in hybrid mode aerial working vehicle (HMAWV) is adopted. The objective is to increase its working domain and decrease the cost under the constraint of enough strength, and the design variables are geometric dimensions. NLPQL and NSGA-II are synthesized to achieve optimal solutions. The results indicated that this integrated method was more efficient than enumerative search algorithm. NSGA-II could approximate the global Pareto front precisely, and the relative error between NLPQL and NSGA-II is trivial. Therefore, this integrated method is effective and shows a potential in engineering applications.
multi-objective optimization fem analysis nsga-ii experimental stress analysis nlpql algorithm