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为提高电力机车二系支承载荷调整优化算法的实用性,解决单一目标遗传算法调整计算产生二系支承点加垫数和加垫总量过多的问题,提出了一种基于多目标遗传算法的寻优方法。针对机车二系调簧问题的偏好结构特点,建立了多目标优化模型,并设计了基于多目标遗传算法的调簧目标函数,进一步引入了适应性权重方法来确定目标函数值,并确立了相应的适应度评价和分配方法。对国产SS3b和HXD1B型机车的应用结果表明:该方法不仅能够优化二系载荷分布,而且可控制加垫量减少约48%,显著提高了调簧算法的实用性和可靠性。
In order to improve the practicability of load adjustment and optimization algorithm of electric locomotive secondary load and to solve the problem of adjustment and calculation of single target genetic algorithm to generate two-series support points plus padding and excessive padding, a multi-objective genetic algorithm Search method. Aiming at the preference structural characteristics of locomotive secondary spring, a multi-objective optimization model is established and the objective function of transfer spring based on multi-objective genetic algorithm is designed. The adaptive weighting method is further introduced to determine the objective function value and the corresponding The fitness evaluation and distribution method. The application results of domestic SS3b and HXD1B locomotives show that this method can not only optimize the secondary load distribution, but also reduce the padding amount by about 48%, which significantly improves the practicability and reliability of the shunting algorithm.