Title: The solution of traffic flow organisation optimisation model based on adaptive genetic algorithm

Authors: Ji Zhang; Hongxia Lv; Boer Deng; Wenxian Wang

Addresses: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China ' School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China ' School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China ' School of Railway Tracks and Transportation, Wuyi University, Jiangmen, 529020, China

Abstract: In order to reduce the workload of the stations along the way, the train flow in the loading area is rationally organised. By designing a vehicle flow organisation method that increases the turnover speed of trucks, it helps to better coordinate the flow of goods and trains. The organisation of the three trucks in the loading area and the time consumption index are analysed, and the optimisation model of the train route adjustment is constructed based on the results to reduce the time consumption of train transportation. In order to ensure the spatial feasibility of the designed model in the application process, based on the improved genetic algorithm, the complexity of the built model and related constraints are considered, and an algorithm that restricts the space search is established. This algorithm can realise adaptive adjustment. The case analysis of Huangdao loading area proves the effect of this model.

Keywords: car flow organisation in loading area; vehicle hour consumption; optimisation model; spatial search strategy; adaptive genetic algorithm.

DOI: 10.1504/IJHVS.2022.128917

International Journal of Heavy Vehicle Systems, 2022 Vol.29 No.5, pp.480 - 502

Received: 05 Jun 2021
Accepted: 13 Sep 2021
Published online: 10 Feb 2023 *

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