考虑工作量平衡的餐饮垃圾多行程收运路线优化

doi:10.16097/j.cnki.1009-6744.2023.06.024

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (6): 239-249.DOI: 10.16097/j.cnki.1009-6744.2023.06.024

考虑工作量平衡的餐饮垃圾多行程收运路线优化

张燕^*，李子鑫，刘进平

大连海事大学，交通运输工程学院，辽宁大连 116026

收稿日期:2023-08-21 修回日期:2023-09-05 接受日期:2023-09-12 出版日期:2023-12-25 发布日期:2023-12-23
作者简介:张燕(1982- )，女，陕西凤翔人，副教授。
基金资助:
国家自然科学基金(71871036，71971035)。

Multi-trip Food Waste Collection Routing Optimization with Workload Balance

ZHANG Yan^*,LI Zi-xin,LIU Jin-ping

School of Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China

Received:2023-08-21 Revised:2023-09-05 Accepted:2023-09-12 Online:2023-12-25 Published:2023-12-23
Supported by:
National Natural Science Foundation of China (71871036，71971035)。

摘要/Abstract

摘要： 城市餐饮垃圾的收运成本居高不下，严重阻碍了垃圾分类的推进。本文首先根据餐饮垃圾的产生及收运特点，划分不同的收运时段和频率，以均衡各个时段的收运量。其次，将城市餐饮垃圾的收运问题建模为带有时间窗的多行程车辆路径问题，并考虑驾驶员的工作量平衡约束。对于小规模问题，通过求解所建立的混合整数规划模型得到问题的最优解；对于大规模问题，针对多车多行程的问题特点，设计三维矩阵编码，提出混合自适应大邻域搜索算法。通过不同规模的算例验证了模型的正确性和算法的有效性。算例结果表明，增加不超过2%的收运成本能大幅度提高驾驶员之间的工作量平衡性。最后，采用大连市中山区的实例将本文所提算法与实际应用的优化算法进行比较发现，当使用不同的收运频率并考虑工作量平衡及城市路网的交通拥堵情况时，采用本文所提出的算法能降低14.3%的收运成本，减少12.7%的碳排放量，同时，将驾驶员之间的工作平衡性提升57.3%。

关键词: 城市交通, 多行程车辆路径问题, 大邻域搜索算法, 餐饮垃圾收运, 工作量平衡

Abstract: The high cost of food waste collection restricts the implementation of waste separation management in the cities. This study determined the time periods and collection frequencies to balance the workload of food waste collection for each time period based on the amount and distribution of the wasted food. The study then modeled the problem as multi-trip vehicle routing problem with time windows and considered the drivers' workload balance. The mixed integer programming model was solved to obtain the optimal solution for the small-size problems. The threedimensional matrix code and the hybrid adaptive large neighborhood search algorithm (HALNS) for multi-trip vehicle routing was used to solve the large-size problems. Five different numerical examples were used to test the mathematical model and the HALNS algorithm. It was found that when considering workload balance constraints, the imbalance of workload among different truck drivers could be improved significantly with less than 2% cost increases. Then, the proposed method was applied in a real case in Dalian of China. The solutions obtained by the HALNS were compared to the existing waste collection optimization tool. The results showed that the collection route obtained by HALNS could reduce collection costs by 14.3% , decrease carbon emissions by 12.7% and improve the balance of driver workloads by 57.3%.

Key words: urban traffic, multi-trip vehicle routing optimization, large neighborhood search algorithm, food waste collection, workload balance

中图分类号:

U121

张燕, 李子鑫, 刘进平. 考虑工作量平衡的餐饮垃圾多行程收运路线优化[J]. 交通运输系统工程与信息, 2023, 23(6): 239-249.

ZHANG Yan, LI Zi-xin, LIU Jin-ping. Multi-trip Food Waste Collection Routing Optimization with Workload Balance[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(6): 239-249.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2023.06.024

http://www.tseit.org.cn/CN/Y2023/V23/I6/239

参考文献

[1] 邴君妍, 罗恩华, 金宜英, 等. 中国餐厨垃圾资源化利用系统建设现状研究[J]. 环境科学与管理, 2018, 43 (4): 39-43. [BING J Y, LUO E H, JIN Y Y, et al. Current situation of food waste recycling in China[J]. Environmental Science and Management, 2018, 43(4): 39-43.]

[2] MATL P, HARTL R F, VIDAL T. Workload equity in vehicle routing: The impact of alternative workload resources[J]. Computers & Operations Research, 2019, 110: 116-129.

[3] LEI C, JIANG Z T, OUYANG Y F. A discrete-continuous hybrid approach to periodic routing of waste collection vehicles with recycling operations[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(12): 5236-5245.

[4] ASEFI H, SHAHPARVARI S, CHHETRI P, et al. Variable fleet size and mix VRP with fleet heterogeneity in integrated solid waste management[J]. Journal of Cleaner Production, 2019, 230: 1376-1395.

[5] ALIHMADI S Z, BARZINPOUR F, PISHVAEE M S. A novel bi-objective credibility-based fuzzy model for municipal waste collection with hard time windows[J]. Journal of Cleaner Production, 2021, 296: 126364. DOI: 10.1016/j.jclepro.2021.126364.

[6] 闫芳, 邓德萍, 柴福良, 等. 考虑环境负效应的智能垃圾桶动态收运路径优化问题[J]. 交通运输系统工程与信息, 2023, 23(1): 265-274. [YAN F, DENG D P, CHAI F L, et al. Optimization of dynamic collection route of smart garbage bins considering negative environmental effects[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(1): 265-274.]

[7] 李明月, 李俐频, 左薇, 等. 基于GIS与改进蚁群算法的垃圾收运路径规划[J]. 环境工程学报, 2022, 16(7): 2388-2396. [LI M Y, LI L P, ZUO W, et al. Garbage collection and transportation path planning based on GIS and improved ant colony algorithm[J]. Chinese Journal of Environmental Engineering, 2022, 16(7): 2388-2396.]

[8] GLAESER S, STUECKEN M. Introduction of an underground waste container system-model and solution approaches[J]. European Journal of Operational Research, 2021, 295(2): 675-689.

[9] FRANCOIS V, ARDA Y, CRAMA Y, et al. Large neighborhood search for multi-trip vehicle routing[J]. European Journal of Operational Research, 2016, 255(2): 422-441.

[10] 彭勇, 高鹤. 带时间窗的多行程交换箱甩挂路径优化[J]. 交通运输系统工程与信息, 2020, 20(1): 166-174. [PENG Y, GAO H. Path optimization of multi-trip swap-body vehicle routing problem with time window[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(1): 166-174.]

[11] PAN B B, ZHANG Z Z, LIM A. Multi-trip time-dependent vehicle routing problem with time windows[J]. European Journal of Operational Research, 2021, 291(1): 218-231.

[12] SHAW P. Using constraint programming and local search methods to solve vehicle routing problems, Berlin, Heidelberg, 1998[C]. Pisa, Italy: Springer Berlin Heidelberg, 1998.

[13] YANG Y, BAO W Q, XIE G H. Estimate of restaurant food waste and its biogas production potential in China [J]. Journal of Cleaner Production, 2019, 211: 309-320.

[14] BARTH M, YOUNGLOVE T, SCORA G. Development of a heavy-duty diesel modal emissions and fuel consumption model[R]. UC Berkeley: Institute of Transportation Studies, 2005.

[15] ZHU L, HU D W. Study on the vehicle routing problem considering congestion and emission factors[J]. International Journal of Production Research, 2019, 57 (19): 6115-6129.

[16] WANG J, RAKHA H A. Fuel consumption model for heavy duty diesel trucks: Model development and testing [J]. Transportation Research Part D: Transport and Environment, 2017, 55: 127-141.

[17] 薛星群, 王旭坪, 詹林敏. 电子商务物流最后一公里配送的碳排放研究 [J]. 运筹与管理, 2019, 28(12): 6. [XUE X Q, WANG X P, ZHAN L M. Study on the carbon emission of e-logistics"Last Mile"delivery[J]. Operations Research and Management Science, 2019, 28(12): 6.]

考虑工作量平衡的餐饮垃圾多行程收运路线优化

Multi-trip Food Waste Collection Routing Optimization with Workload Balance

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	周备, 张莹, 张生瑞, 周千喜, 汪琴. 基于生成对抗网络的追尾事故数据填补方法研究[J]. 交通运输系统工程与信息, 2024, 24(1): 132-137.
[2]	王维莉, 肖雨晴, 周辉, 张为四. 无信控交叉口电动自行车与机动车的冲突博弈研究[J]. 交通运输系统工程与信息, 2024, 24(1): 149-158.
[3]	胡立伟, 张瑞杰, 赵雪亭, 贺雨, 陈琛, 刘冰, 侯智. 道路环形交叉口机动车冲突风险区识别模型研究[J]. 交通运输系统工程与信息, 2024, 24(1): 168-178.
[4]	张英贵, 赵明慧, 张云丽. 面向虚拟连挂的城轨列车群组追踪运行仿真研究[J]. 交通运输系统工程与信息, 2024, 24(1): 199-209.
[5]	郝妍熙, 卫书彤, 胡华, 王润祺, 刘志钢. 地铁车站步行障碍行人避让行为建模与进出站仿真[J]. 交通运输系统工程与信息, 2024, 24(1): 210-220.
[6]	翁剑成, 张云飞, 林鹏飞, 李文杰. 基于就医活动推断的老年人公交就医可达性研究[J]. 交通运输系统工程与信息, 2024, 24(1): 221-229.
[7]	孙小慧, 黄诚允. 外卖配送电动自行车换电柜选址定容实证研究[J]. 交通运输系统工程与信息, 2024, 24(1): 230-239.
[8]	葛显龙, 王博, 杨育树, 杨昙月, 尹作发. 考虑出行特征的电动汽车协同充电调度优化研究[J]. 交通运输系统工程与信息, 2024, 24(1): 240-252.
[9]	吴静娴, 唐桂孔, 李文翔. 建成环境对共享单车分时骑行量的非线性作用研究：以上海市为例[J]. 交通运输系统工程与信息, 2024, 24(1): 290-298.
[10]	邓毛颖, 邓策方. 基于结构、效率、公平与韧性的路网密度适宜性评价研究[J]. 交通运输系统工程与信息, 2023, 23(6): 22-32.
[11]	荆彬彬, 林永杰, 阎珠豪, 黄政杰. 非闭合交通路网路径选择与绿波协调同步优化方法[J]. 交通运输系统工程与信息, 2023, 23(6): 51-62.
[12]	张兵, 陶文康, 刘建荣, 薛运强, 邓明君. 有限理性视域下老年人出行方式选择巢式Logit模型[J]. 交通运输系统工程与信息, 2023, 23(6): 74-82.
[13]	彭金栓, 袁浩, 宋臻, 范子斌, 杨祥浩, 张磊. 等待阶段使用手机对行人过街风险的影响[J]. 交通运输系统工程与信息, 2023, 23(6): 83-89.
[14]	张文会, 徐海彬, 周舸, 温文. 信控交叉口行人过街冲突严重程度评价模型[J]. 交通运输系统工程与信息, 2023, 23(6): 89-99.
[15]	王伊凡, 陈学武. 考虑空间效应的公交站点客流量影响因素分析[J]. 交通运输系统工程与信息, 2023, 23(6): 153-164.