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收货时间窗软约束下绿色多式联运路径优化
引用本文:陈钉均,李尧,倪少权,杨尧.收货时间窗软约束下绿色多式联运路径优化[J].计算机仿真,2020,37(4):209-214.
作者姓名:陈钉均  李尧  倪少权  杨尧
作者单位:西南交通大学交通运输与物流学院,四川成都610031;综合交通运输智能化国家地方联合工程实验室,四川成都610031;西南交通大学交通运输与物流学院,四川成都610031;四川公路工程咨询监理有限公司,四川成都610000
基金项目:中国铁路总公司科技研究项目;四川省科技计划;国家自然科学基金;成都市软科学研究计划;国家重点研发计划
摘    要:绿色多式联运不仅能有效降低物流成本,提升物流效率,而且能减少环境污染,随着我国综合运输体系的建设与完善,对绿色多式联运的研究已成为热点问题。针对带收货时间窗的绿色多式联运路径选择问题,将收货时间窗作为软约束,运输时限与收货人满意度结合,同时考虑基于运输成本大小的承运人满意度,构建了满意度权重不确定的绿色多式联运路径选择模型。通过Matlab仿真求解,结果表明,模型对运输时限与收货时间窗的关系把控合理,兼顾了承运人和收货人双方的利益。针对不同的运输货物,通过调整双方满意度权重可以得出更加切合实际的最优运输路径,运输时间不拘泥于固定收货时间窗内,且在运输费用上具有明显的优越性。

关 键 词:综合交通运输  路径优化  蚁群算法  时间窗软约束  碳排放

Optimal Path of Green Multimodal Transport under Soft Constraint of Receipt Time Window
CHEN Ding-jun,LI Yao,NShao-quan,YANG Yao.Optimal Path of Green Multimodal Transport under Soft Constraint of Receipt Time Window[J].Computer Simulation,2020,37(4):209-214.
Authors:CHEN Ding-jun  LI Yao  NShao-quan  YANG Yao
Affiliation:(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu Sichuan 610031,China;National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation,Southwest Jiaotong University,Chengdu Sichuan 610031,China;Sichuan Highway Engineering Consult Supervision Company Ltd.,Chengdu Sichuan 610000,China)
Abstract:Green multimodal transport can effectively reduce logistics costs, improve logistics efficiency, and reduce environmental pollution. With the construction and improvement of China’s comprehensive transportation system, the research on green multimodal transport has become a hot issue. In order to solve the problem of green multimodal transport path selection with receiving time window, this paper constructed a green multimodal transport path selection model based on carrier satisfaction and consignee satisfaction weight uncertainty. In this paper, the receiving time window was used as a soft constraint, the transportation time was combined with consignee satisfaction, and the carrier satisfaction based on the transportation cost was considered. The Matlab software was used to solve the problem. The experimental results show that the model in this paper is more flexible. For different shipments, adjusting the satisfaction weight can lead to a more realistic and optimal transportation path. The transportation time is not limited to the time window of receipt, and the optimal path is superior to the optimal path with the receiving time window as a strong constraint. The model of this paper is practical, and the relationship between transportation time and receiving time window is controlled reasonably, taking into account the interests of both the carrier and the consignee.
Keywords:Integrated transportation  Routing optimization  Ant colony algorithm  Time window soft constraint  Carbon emission
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