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高速铁路快运末端货物取送一体化优化研究

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随着我国快递业务量的持续增长和客户对快递服务水平要求的不断提高,传统的航空快递运输成本较高、运输条件限制多,公路快递运输能耗高、排放大的不足越发明显,制约了行业的快速发展.通过使用高速铁路承担快运货物的干线运输任务,优化高速铁路与城市相衔接的末端取送货网络,可以提高快运货物的运输效率和客户满意度.在高速铁路快运末端取送货网络设计的基础上,以最小化运输成本和最大化客户满意度为优化目标,建立上层转运与下层取配的双层多目标优化模型.针对模型多目标的特点,设计基于非支配排序的遗传算法NSGA-Ⅱ,并改进,使其适用于求解双层优化问题.对本文所提方法进行验证,求解结果显示,算法平均55.9代收敛,最终得到的Pareto最优解集中包括10个拥挤度在0.5左右的解,高速铁路快运次日达要求满足率最高为97%,最低为92%,平均值为94.3%.
Research on Optimization of Terminal Cargo Integrated Pickup and Delivery for High-speed Railway Express
With the continuous growth of express delivery volume in China and the increasing customer demands for ex-press service level,the shortcomings of the traditional air express transportation with higher costs and more transportation restrictions,and road express transportation with high energy consumption and emissions are becoming increasingly obvi-ous,which restricts the further development of the express delivery industry.By using high-speed railway to undertake the trunk transportation tasks of express goods and optimizing the terminal pick-up and delivery network that connects high-speed railway with urban areas,transportation efficiency and customer satisfaction can be improved.Based on the design of high-speed railway express terminal pick-up and delivery network,this paper established a double-layer multi-objective optimization model with the upper layer of transshipment and lower layer of pick-up and distribution with the optimization objectives of minimizing transportation cost and maximizing customer satisfaction.Considering the multi-ob-jective characteristics of the model,a non-dominated sorting genetic algorithm,NSGA-Ⅱ,was designed and improved for solving bi-level optimization problems.The proposed method was verified,and the solution results show that the algo-rithm converges at 55.9 generations on average,and the final pareto optimal solution set includes 10 solutions with crow-ding distance around 0.5.Among these solutions,the highest satisfaction rate of meeting the requirement for high-speed railway next-day delivery is 97%,with the lowest of 92%,and the average of 94.3%.

high-speed railway expressterminal pickup and deliverybi-level programming modelNSGA-Ⅱ algorithmmulti-objective optimization

李东颖、王力、朱晓宁、刘文茜、闫伟、李会玲

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北京交通大学交通运输学院,北京 100044

北京交通大学综合交通运输理论行业重点实验室,北京 100044

中国国家铁路集团有限公司办公厅,北京 100084

中铁快运股份有限公司北京分公司,北京 100070

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高速铁路快运 末端取送货 双层规划模型 NSGA-Ⅱ算法 多目标优化

国家自然科学基金

U2034208

2024

铁道学报
中国铁道学会

铁道学报

CSTPCD北大核心
影响因子:0.9
ISSN:1001-8360
年,卷(期):2024.46(6)
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