Optimization Algorithm for Urban Rail Transit Operation Scheduling based on Linear Programming

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI:10.12694/scpe.v24i3.2245
Shuang Wu, Jinlong Wu, Yifeng Sun, Tong Yao
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Abstract

At present, the traditional urban public transportation system cannot meet people’s daily travel needs. Urban Rail Transit (URT) has been rapidly promoted in major cities due to its advantages such as low energy consumption, high frequency, and large traffic volume. To achieve a more excellent and energy-saving operation scheduling strategy, the research first combines the train dynamics model and the energy consumption model. Since the optimization problem of URT is a linear problem, the attraction model of the Firefly algorithm can determine the calculation time consumed by the algorithm, which is very suitable for the complex optimization problem of URT. Therefore, the FA based optimization algorithm for urban rail transit operation scheduling (FURTOSO) based on the Firefly algorithm is studied and designed. Therefore, based on the study of the four working conditions of traction, cruise, coasting, and braking, a Firefly Algorithm for Urban Rail Transit Operation Scheduling (FURTOSO) was designed. Finally, the study optimizes the operation scheduling of Chengdu Metro Line 8 from two aspects: driving strategy and train schedule. The research demonstrates that the FURTOSO algorithm only needs 76 iterations to reach a stable state, with a fitness value of 0.6827. In practical applications, the utilization rate of train RBE is 30.1%, the total energy consumption (TEC) is 2.661 * 1011J, and the energy saving rate is 13.03%. In summary, the FURTOSO algorithm proposed in the study has excellent performance and has better energy-saving effects in Chengdu Metro Line 8.
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基于线性规划的城市轨道交通运营调度优化算法
目前,传统的城市公共交通系统已经不能满足人们的日常出行需求。城市轨道交通以其能耗低、频率高、交通量大等优点在各大城市得到迅速推广。为了实现更优、更节能的运行调度策略,本研究首先将列车动力学模型与能耗模型相结合。由于轨道交通优化问题是一个线性问题,萤火虫算法的吸引力模型可以确定算法所消耗的计算时间,非常适合复杂的轨道交通优化问题。为此,研究设计了基于萤火虫算法的基于FA的城市轨道交通运营调度优化算法(FURTOSO)。因此,在对牵引、巡航、滑行、制动四种工况进行研究的基础上,设计了城市轨道交通运行调度的萤火虫算法(FURTOSO)。最后,从行车策略和列车调度两个方面对成都地铁8号线运营调度进行优化。研究表明,FURTOSO算法只需76次迭代即可达到稳定状态,适应度值为0.6827。在实际应用中,列车RBE利用率为30.1%,总能耗(TEC)为2.661 * 1011J,节能率为13.03%。综上所述,本文提出的FURTOSO算法性能优异,在成都地铁8号线中具有较好的节能效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scalable Computing-Practice and Experience
Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.00
自引率
0.00%
发文量
10
期刊介绍: The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.
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