Approximate multi-objective optimization using conservative and feasible moving least squares method: application to automotive knuckle design

作者：Song Chang Yong; Choi Ha Young; Lee Jongsoo^*

来源：Structural and Multidisciplinary Optimization, 2014, 49(5): 851-861.

DOI：10.1007/s00158-013-1009-3

• Approximate multi-objective optimization
• Pareto optimal solutions
• Conservativeness and feasibility
• Moving Least Squares Method (MLSM)
• Conservative and Feasible MLSM (CF-MLSM)

The original version of the moving least squares method (MLSM) does not always ensure solution feasibility for nonlinear and/or non-convex functions in the context of meta-model-based approximate optimization. The paper explores a new implementation of MLSM that ensures the conservative feasibility of Pareto optimal solutions in non-dominated sorting genetic algorithm (NSGA-II)-based approximate multi-objective optimization. We devised a 'conservative and feasible MLSM' (CF-MLSM) to realize the conservativeness and feasibility of multi-objective Pareto optimal solutions for both unconstrained and constrained problems. We verified the usefulness of our proposed approach by exploring strength-based sizing optimization of an automotive knuckle component under bump and brake loading constraints.

• 出版日期2014-5