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

被引：0
作者：
Chang Yong Song
Ha-Young Choi
Jongsoo Lee
机构：
[1] Mokpo National University,Department of Ocean Engineering
[2] Dongyang Mirae University,Department of Mechanical Engineering
[3] Yonsei University,School of Mechanical Engineering
来源：
Structural and Multidisciplinary Optimization | 2014年 / 49卷
关键词：
Approximate multi-objective optimization; Pareto optimal solutions; Conservativeness and feasibility; Moving Least Squares Method (MLSM); Conservative and Feasible MLSM (CF-MLSM);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：851 / 861
页数：10
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