| 基于海铁联运的集装箱班列服务路径优化 |
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| 引用本文： | 张丰婷, 杨菊花, 于江, 秦永胜, 沈发才. 基于海铁联运的集装箱班列服务路径优化[J]. 交通信息与安全, 2021, 39(4): 125-133. doi: 10.3963/j.jssn.1674-4861.2021.04.016 |
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| 作者姓名： | 张丰婷 杨菊花 于江 秦永胜 沈发才 |
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| 作者单位： | 1.兰州交通大学交通运输学院 兰州 730070;2.乌鲁木齐集团有限公司乌鲁木齐车务段 乌鲁木齐 830000 |
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| 基金项目： | 甘肃省自然科学基金项目20JR5RA394 |
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| 摘 要： | 虑考虑海铁联运过程中影响集装箱班列开行的不确定因素, 结合班列服务客户各自固定需求时间窗的实际需求, 引入不确定规划区间来表示集装箱在客户节点的装卸箱服务时间, 同时将具有时效性要求的需求时间窗设置为软约束, 运用惩罚函数将其作为惩罚项整合到运输成本目标函数中, 选择合理的惩罚系数, 构建以运输成本低、运输时间少为目标的班列服务路径非线性多目标优化模型, 针对不确定变量, 采用机会约束规划转换模型得到考虑模糊时间的多目标路径优化模型, 通过加权求和将多目标合并转化为单目标问题, 并设计人工蜂群算法求解所构建的班列服务路径优化模型, 并以盐田港海铁联运为实例进行了模型检验和对比分析。结果表明: (1)在硬时间窗约束下运输时间减少了88%, 但成本增加了97%, 充分表明了软时间窗设置的优势; (2)考虑不同的运输目标时, 只考虑运输费用时, 运输时间增加了5.3%;只考虑运输时间时, 运输费用增加了67.8%。所建模型和算法能够很好的满足不同客户不同运输时效性的需求, 在运输费用方面具有明显的优越性。
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| 关 键 词： | 交通规划 路径优化 不确定规划 时间窗软约束 人工蜂群算法 |
| 收稿时间： | 2021-01-22 |
Optimization of Container Train Service Route Based on Sea-Rail Intermodal Transportation |
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| ZHANG Fengting, YANG Juhua, YU Jiang, QIN Yongsheng, SHEN Facai. Optimization of Container Train Service Route Based on Sea-Rail Intermodal Transportation[J]. Journal of Transport Information and Safety, 2021, 39(4): 125-133. doi: 10.3963/j.jssn.1674-4861.2021.04.016 |
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| Authors: | ZHANG Fengting YANG Juhua YU Jiang QIN Yongsheng SHEN Facai |
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| Affiliation: | 1. School of Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China;2. Urumqi Train Department of Urumqi Group Co., Ltd., Urumqi 830000, China |
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| Abstract: | Since uncertain factors are affecting the operation of container trains in the process of sea-rail intermodaltransportation.Combined with the customers’ demand for a fixed time window , the uncertain planning interval is introduced to represent the range of time in container loading and unloading at each customer node.Meanwhile,the demand time window with timeliness requirements is set as a soft constraint. The penalty function is integrated into theobjective function of the transportation cost as a penalty term. A reasonable penalty coefficient is selected to constructa multi-objective optimization model of the train service path combined with the low transportation cost and less transportation time. For uncertain variables,the chance-constrained programming transformation model is used to obtain amulti-objective path optimization model considering fuzzy time. Then, the multi-objective problem is transformed intoa single objective problem by weighted summation, and the artificial bee colony algorithm is designed to solve the constructed model.The results of sea-rail intermodal transportation in Yantian Port show that:① The transportation timeis reduced by 88% in the constraint of hard time windows, but the cost is increased by 97%,fully showing the advantage of soft time windows.② When only the transportation cost is considered,the transportation time increases by5.3%. When only the transportation time is considered , the transportation cost increases by 67.8%.These experimental results confirm that the proposed model reduces the transportation cost and meets the needs of different transportation timeliness of different customers. |
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| Keywords: | transportation planning route optimization uncertain planning constraint of soft time windows artificial bee colony algorithm |
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