基于差异演化算法的动压滑动轴承多目标优化

Multi-objective Optimization of Hydrodynamic Sliding Bearing Based on Differential Evolution Algorithm

为研究流体动压轴承的多目标优化问题,提出一种改进多目标差异演化算法。该算法在选择差分向量时,对产生差分向量的两个个体比较其优劣,用非支配解减去支配解,引导个体向非劣解进化,提高算法的收敛速度;其次提出了种群修剪策略,消除进化后期种群中相同个体引起的种群全局搜索能力下降的缺点,以提升算法的全局寻优能力。通过与其它算法的比较,发现该算法能有效避免'早熟'收敛,具有较好的收敛速度和多样性。工程实例求解结果表明了算法的工程可行性。

In order to solve multi-objective optimization problem of the hydrodynamic sliding bearing, a modified multi-objective differential evolution algorithm （MMODE） was proposed. The proposed algorithm provided a modified differential vector selection mechanism to improve the convergence speed and a population pruning strategy to maintain the population diversity. The vector selection mechanism compared two selected individuals and used the non-dominated individual minus the domination individual. Compared with several other evolutionary algorithms, the results showed that the proposed algorithm could overcome the premature convergence efficiently and had better convergence and diversity metrics. The results of engineering example showed the feasibility of the proposed algorithm.