列车节能运行问题的改进头脑风暴优化算法

B. Qu, Qian Zhou, Yongsheng Zhu, Jing J. Liang, C. Yue, Y. Jiao, Li Yan, P. N. Suganthan
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引用次数: 2

摘要

提出了一种利用改进的脑风暴优化算法确定列车最优行驶策略的新方法。该方法利用成功父选择框架的思想对原有的头脑风暴优化算法进行改进,避免了在处理复杂问题时进化过程中的过早收敛。该算法的目标是通过寻找切换点来最小化列车的能量消耗。此外,还考虑了限速、坡度、最大加减速以及最大牵引力和制动力随速度的变化,以满足实际约束条件。最后通过四种算法的对比仿真表明,在相同条件下,采用IBSO算法得到的列车节能运行策略更为优越。
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An improved brain storm optimisation algorithm for energy-efficient train operation problem
This paper presents a new method to determine the optimal driving strategies of the train using an improved brain storm optimisation (IBSO) algorithm. In the proposed method, the idea of successful-parent-selecting frame is applied to improve the original brain storm optimisation (BSO) algorithm avoiding premature convergence in evolutionary process while dealing with complex problems. The objective of the algorithm is to minimise energy consumption of the train by finding the switching points. Furthermore, the speed limits, gradients, maximum acceleration and deceleration as well as the maximum traction and braking force varying with speed are taken into consideration to meet practical constraints. Finally the comparison simulations among four algorithms show that the energy-efficient train operation strategy obtained by IBSO algorithm are more superior under the same conditions.
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