计算机应用 ›› 2020, Vol. 40 ›› Issue (3): 883-890.DOI: 10.11772/j.issn.1001-9081.2019071306

• 应用前沿、交叉与综合 • 上一篇    下一篇

考虑拥堵区域的多车型绿色车辆路径问题优化

赵志学1,2, 李夏苗1, 周鲜成2   

  1. 1. 中南大学 交通运输工程学院, 长沙 410083;
    2. 移动商务智能湖南省重点实验室(湖南工商大学), 长沙 410205
  • 收稿日期:2019-07-30 修回日期:2019-10-03 出版日期:2020-03-10 发布日期:2018-07-16
  • 通讯作者: 赵志学
  • 作者简介:赵志学(1982-),男,河北唐山人,讲师,博士研究生,主要研究方向:交通运输规划、智能优化;李夏苗(1963-),男,湖南茶陵人,教授,博士,主要研究方向:物流企业管理、运输系统分析与决策;周鲜成(1965-),男,湖南双峰人,教授,博士,主要研究方向:优化理论与方法、智能物流。
  • 基金资助:
    国家自然科学基金资助项目(61304253, 61403426);教育部人文社科基金资助项目(14YJCZH099)。

Green vehicle routing problem optimization for multi-type vehicles considering traffic congestion areas

ZHAO Zhixue1,2, LI Xiamiao1, ZHOU Xiancheng2   

  1. 1. School of Traffic&Transportation Engineering, Central South University, Changsha Hunan 410083, China;
    2. Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Technology and Business, Changsha Hunan 410205, China
  • Received:2019-07-30 Revised:2019-10-03 Online:2020-03-10 Published:2018-07-16
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61304253, 61403426), the Foundation of Humanities and Social Sciences of Ministry of Education (14YJCZH099).

摘要: 针对降低物流配送过程中产生的碳排放问题,从绿色环保角度出发,提出一种考虑交通拥堵区域的多车型物流配送车辆的绿色车辆路径问题(GVRP)。首先分析不同类型车辆、不同拥堵状况对车辆行驶路线规划的影响,然后引入基于车辆行驶速度和载重的碳排放速率度量函数;其次以车辆管理使用费用和油耗碳排放成本最小作为优化目标,构建双目标绿色车辆路径模型;最后根据模型的特点设计一种融合模拟退火算法的混合差分进化算法对问题进行求解。通过实验仿真验证模型和算法可以有效规避拥堵区域,与只使用单一4 t车型配送相比,所提模型总成本降低了1.5%,油耗碳排放成本降低了4.3%;和以行驶距离最短为目标的模型相比,所提模型的总配送成本降低了8.1%。说明该模型提高物流企业的经济效益也促进了节能减排。同时所提算法与基本差分算法相比,总配送成本可以降低3%~6%;与遗传算法相比,优化效果更明显,总配送成本可以降低4%~11%,证明该算法更具有优越性。综上所提模型和算法可以为物流企业城市配送路径决策提供良好的参考依据。

关键词: 绿色车辆路径, 能耗, 碳排放成本, 混合差分进化算法, 拥堵

Abstract: In order to reduce the carbon emission of vehicles during the process of logistics distribution, on the perspective of green environmental protection, a Green Vehicle Routing Problem (GVRP) of logistics distribution vehicles with multi-type vehicles considering traffic congestion areas was analyzed. Firstly, the effect of multi-type vehicles and different traffic congestion situations on the vehicle route planning was investigated. Secondly, the metric function of carbon emission rate was introduced on the basis of vehicle speed and load. Thirdly, a dual-objective green vehicle routing model with minimizing the vehicle management cost as well as the fuel consumption and carbon emission cost as optimization objects was established. Finally, a hybrid differential evolution algorithm combined with simulated annealing algorithm was designed to solve the problem. Simulation results verify that the model and algorithm can effectively avoid the congestion areas. Compared to the simulation results only using 4 t vehicles for distribution, the proposed model has the total cost reduced by 1.5%, and the fuel consumption and carbon emission cost decreased by 4.3%. Compared the model with optimization objective of shortest driving distance, the proposed model has the total distribution cost decreased by 8.1%, demonstrating that the model can improve the economic benefits of logistics enterprises and promote the energy saving and emission reduction. At the same time, compared with the basic differential algorithm, the hybrid differential evolution algorithm with simulated annealing algorithm can reduce the total transportation cost by 3% to 6%; compared with the genetic algorithm, the proposed algorithm has more obvious optimization effect, and has the total transportation cost reduced by 4% to 11%, proving the superiority of the algorithm. In summary, the proposed model and algorithm can provide effective advices for the urban distribution routing decision of logistics enterprises.

Key words: green vehicle routing, energy consumption, carbon emission cost, hybrid differential evolution algorithm, congestion

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