基于多准则决策的减振弹簧多目标优化

Multi-objective Optimization Design of Shock Absorber Spring Based on Multi-criteria Decision

为实现弹簧轻量化及高疲劳寿命的多目标优化,采用多目标遗传算法求出问题的帕莱托解集,通过后期决策得到不同偏好下的最优解。结果表明:优化后的弹簧轻,寿命长,而且采用先寻优后决策的求解模式,能有效弱化先验知识不足的影响,避免局部最优问题,较传统多目标优化方法更为实用有效。

For decreasing spring＇s mass and increasing the life of fatigue, MOGA （multi-object genetic algorithm） is applied to obtain the pareto results of multi-objective optimization of Shock absorber spring, and choose the best answer according to multi-criteria decision. The results show the mass decreases and the life increases through optimization design. Furthermore, The pattern, making decision after searching optimum solutions, is more effective and can weak designer＇ s transcendental information deficiency problem and avoid the local optimal,which is a main problem of simplified multi-objective optimization.