基于能耗、碳排放油电车辆混合最优配置策略

PDF (PC)

基于能耗、碳排放油电车辆混合最优配置策略

Optimal allocation strategy for fuel-electric vehicles based on energy consumption and carbon emissions

基于能耗、碳排放油电车辆混合最优配置策略

Optimal allocation strategy for fuel-electric vehicles based on energy consumption and carbon emissions

摘要/Abstract

参考文献

多维度评价

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 3

多维度评价

本文评价

推荐阅读 0

doi:10.6040/j.issn.1672-3961.0.2023.322

山东大学学报 (工学版) ›› 2025, Vol. 55 ›› Issue (1): 15-23.doi: 10.6040/j.issn.1672-3961.0.2023.322

• 机器学习与数据挖掘 • 上一篇

李军涛^1,2,茆俊亚²,侯星星²,郭文文³

1.上海海洋大学经济与管理学院, 上海 201306;2.上海海洋大学工程学院, 上海 201306;3.上海海事大学交通运输学院, 上海 201306

发布日期:2025-02-20
作者简介:李军涛(1974— ),男,湖北荆门人,副教授,硕士生导师,博士,主要研究方向为物流系统调度优化. E-mail:jtli@shou.edu.cn
基金资助:
国家自然科学基金资助项目(71501125);上海市教委重点资助项目(12ZZ167)

LI Juntao^1,2, MAO Junya², HOU Xingxing², GUO Wenwen³

1. College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China;
2. College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China;
3. College of Transport &
Communications, Shanghai Maritime University, Shanghai 201306, China

Published:2025-02-20

摘要： 针对混合车队车辆路径优化问题,考虑电动车多次充电、油电混合车队配置比例及车辆装载量对能耗的影响,以包含油耗成本或电动车能耗成本在内的总成本为目标构建数学模型,提出一种改进的遗传-变邻域模拟退火算法,通过实例验证算法的可行性和准确性。仿真试验表明,与全电动车配送方案相比,油电混合模式的配送成本降低25.8%,时间窗惩罚成本降低91.2%;与全燃油车配送方案相比,油电混合模式的碳排放降低62.2%。针对混合车队路径优化问题模型,相对于传统遗传算法,遗传-变邻域模拟退火算法可以更快求得最优解,验证了算法的有效性。根据油电混合车队配置比例对模型的影响分析可知,最优配置比为1∶1时,可以获取最优解。

关键词: 混合车队, 能耗, 碳排放, 遗传-变邻域模拟退火算法, 油电混合配置策略

中图分类号:

TP301

李军涛,茆俊亚,侯星星,郭文文. 基于能耗、碳排放油电车辆混合最优配置策略[J]. 山东大学学报 (工学版), 2025, 55(1): 15-23.

LI Juntao, MAO Junya, HOU Xingxing, GUO Wenwen. Optimal allocation strategy for fuel-electric vehicles based on energy consumption and carbon emissions[J]. Journal of Shandong University(Engineering Science), 2025, 55(1): 15-23.

[1] VINCENT F Y, JODIAWAN P, GUNAWAN A. An adaptive large neighborhood search for the green mixed fleet vehicle routing problem with realistic energy consumption and partial recharges[J]. Applied Soft Computing, 2021, 105(5): 107251.
[2] KESKIN M, ÇATAY B. A matheuristic method for the electric vehicle routing problem with time windows and fast chargers[J]. Computers & Operations Research, 2018, 100(12): 172-188.
[3] ERDELIC T, CARIC T, ERDELIC M, et al. Electric vehicle routing problem with single or multiple recharges[J]. Transportation Research Procedia, 2019, 40: 217-224.
[4] 葛显龙, 李祖伟, 葛小波. 考虑灵活充电策略的带时间窗物流配送路径优化研究[J]. 控制理论与应用, 2020, 37(6): 1293-1301. GE Xianlong, LI Zuwei, GE Xiaobo. Optimization study of logistics distribution path with time window considering flexible charging strategy[J]. Control Theory and Applications, 2020, 37(6): 1293-1301.
[5] 宋稚雅. 基于纯电动物流车的城市配送车辆路径问题研究[D]. 北京: 北京交通大学, 2019. SONG Zhiya. Research on urban distribution vehicle path problem based on pure electric logistics vehicle[D]. Beijing: Beijing Jiao Tong University, 2019.
[6] BREUNIG U, BALDACCI R, HARTL R F, et al. The electric two-echelon vehicle routing problem[J]. Computers & Operations Research, 2019, 103(3): 198-210.
[7] JIE W, YANG J, ZHANG M, et al. The two-echelon capacitated electric vehicle routing problem with battery swapping stations: formulation and efficient methodology[J]. European Journal of Operational Research, 2019, 272(3): 879-904.
[8] 胡大伟, 刘成清, 胡卉, 等. 基于低碳视角的两阶段开放式选址路径问题:燃油车与电动车对比[J]. 系统工程理论与实践, 2020, 40(12): 3230-3242. HU Dawei, LIU Chengqing, HU Hui, et al. Two-stage open location path problem based on low-carbon perspective: comparison between fuel vehicles and electric vehicles[J]. Systems Engineering Theory and Practice, 2020, 40(12): 3230-3242.
[9] MACRINA G, PUGLIESE L D P, GUERRIERO F, et al. The green mixed fleet vehicle routing problem with partial battery recharging and time windows[J]. Computers & Operations Research, 2019, 101(1): 183-199.
[10] MACRINA G, LAPORTE G, GUERRIERO F, et al. An energy-efficient green-vehicle routing problem with mixed vehicle fleet, partial battery recharging and time windows[J]. European Journal of Operational Research, 2019, 276(3): 971-982.
[11] 范厚明, 杨成, 张跃光, 等. 混合时间窗下多中心混合车队车辆路径优化研究[J]. 计算机集成制造系统, 2023, 29(10): 3529-3546. FAN Houming, YANG Cheng, ZHANG Yueguang, et al. Research on vehicle path optimization for multi-center mixed fleet under hybrid time window[J]. Computer Integrated Manufacturing Systems, 2023, 29(10): 3529-3546.
[12] YU V F, JODIAWAN P, GUNAWAN A, et al. A mathematical programming model for the green mixed fleet vehicle routing problem with realistic energy consumption and partial recharges[C] //Proceedings of the 2019 IEEE International Conference on Industrial Engineering and Engineering Management(IEEM). Piscataway, USA: IEEE, 2019: 1339-1343.
[13] 蔡银怡. 考虑充电策略和非线性能量消耗的电动车配送路径规划研究[D]. 广州: 华南理工大学, 2020. CAI Yinyi. Research on electric vehicle delivery path planning considering charging strategy and nonlinear energy consumption[D]. Guangzhou: South China University of Technology, 2020.
[14] BEKTA?瘙塁 T, LAPORTE G. The pollution-routing problem[J]. Transportation Research Part B: Methodological, 2011, 45(8): 1232-1250.
[15] 李军涛, 刘明月, 刘朋飞. 生鲜农产品多车型冷链物流车辆路径优化[J]. 中国农业大学学报, 2021, 26(7): 115-123. LI Juntao, LIU Mingyue, LIU Pengfei. Optimization of vehicle paths for fresh agricultural products in multi-vehicle cold chain logistics[J]. Journal of China Agricultural University, 2021, 26(7): 115-123.
[16] 赵姣, 杨倩倩, 胡大伟, 等. 基于排队模型的电动物流车充电站选址和运输路径问题[J]. 山东大学学报(工学版), 2024, 54(2): 47-59. ZHAO Jiao, YANG Qianqian, HU Dawei, et al. Location and transportation route problems of charging stations for electric logistics vehicles based on queuing model[J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 47-59.
[17] 王恒, 徐亚星, 王振锋, 等. 基于道路状况的生鲜农产品配送路径优化[J]. 系统仿真学报, 2019, 31(1): 126-135. WANG Heng, XU Yaxing, WANG Zhenfeng, et al. Optimization of fresh produce distribution paths based on road conditions[J]. Journal of System Simulation, 2019, 31(1): 126-135.
[18] 宋修广, 郭鑫铭, 闫方, 等. 公路应急救援车辆智能调度技术[J]. 山东大学学报(工学版), 2023, 53(4): 1-17. SONG Xiuguang, GUO Xinming, YAN Fang, et al. Intelligent scheduling technology of highway emergency rescue vehicle[J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 1-17.
[19] 侯登凯, 范厚明, 任晓雪. 时变路网下多中心混合车队联合配送车辆路径优化[J]. 大连海事大学学报, 2022, 48(1): 11-22. HOU Dengkai, FAN Houming, REN Xiaoxue. Path optimization of joint distribution vehicles in multi-center mixed fleet under time-varying road network[J]. Journal of Dalian Maritime University, 2022, 48(1): 11-22.
[20] GOEKE D, SCHNEIDER M. Routing a mixed fleet of electric and conventional vehicles[J]. European Journal of Operational Research, 2015, 245(1): 81-99.

Viewed

Full text

	From	local

	Times	49
	Rate	100%

Abstract

Just accepted	Online first	Issue

0	0	98

From	Others	local

Times	95	3
Rate	97%	3%

Cited

Web of Science	Crossref	ScienceDirect	Search for Citations in Google Scholar >>


This page requires you have already subscribed to WoS.

Shared

Discussed

Just accepted

Online first

Just accepted

Online first

[1]	孙鸿昌,周风余,单明珠,翟文文,牛兰强. 基于模式划分的空调能耗混合填补方法[J]. 山东大学学报 (工学版), 2022, 52(1): 9-18.
[2]	郝前华1，何清华1,2*，朱俊霖1，李赛白1，陈正1，舒敏飞1. 配置蓄能器的电动叉车液压起升系统能耗试验研究[J]. 山东大学学报(工学版), 2011, 41(6): 80-84.
[3]	徐楠王胜春王秀叶. 一种改进的当量应变能密度方法[J]. 山东大学学报(工学版), 2008, 38(6): 118-120.