考虑时变交通的生鲜待加工农产品运输车辆调度优化

郑加鹏 ,  张立杰 ,  熊宗慧

工业工程 ›› 2026, Vol. 29 ›› Issue (4) : 106 -116.

PDF (1508KB)
工业工程 ›› 2026, Vol. 29 ›› Issue (4) : 106 -116. DOI: 10.3969/j.issn.1007-7375.250113
系统建模与优化

考虑时变交通的生鲜待加工农产品运输车辆调度优化

作者信息 +

Optimization of Vehicle Scheduling for Fresh Agricultural Products to be Processed Considering Time-Varying Traffic

Author information +
文章历史 +
PDF (1544K)

摘要

受高峰期车流量的影响,生鲜待加工农产品运输调度过程中容易引发车辆大规模排队等待问题。为解决交通环境影响下,生鲜待加工农产品运输车辆调度问题,探讨车辆速度变化对车辆排队卸货的影响,构建一种多峰型反向高斯分布的时变速度刻画模型描述交通状态对车速的影响,提出考虑交通环境影响的运输车辆速度时变的生鲜待加工农产品车辆调度优化模型;设计结合正向连续交叉算子和自适应差分变异算子的改进遗传算法,融合高斯分布排队时间倒推机制,利用二分搜索算法对发车时间精准搜索。结果表明,多峰型反向高斯分布的时变速度模型能够较好地刻画模拟运输车辆速度时变特性,所提出的数学优化模型与算法能有效生成车辆调度方案,对保障原料供应质量、提升物流效率具有实践意义。

Abstract

During peak periods, traffic congestion often causes large-scale vehicle queuing in the scheduling of fresh agricultural products to be processed. In order to address this vehicle scheduling problem under time-varying traffic conditions, and to investigate the impact of vehicle speed on vehicle queuing and unloading, a time-varying speed characterization model with a multi-peak inverse Gaussian distribution is constructed to describe the impact of traffic conditions on vehicle speed. A time-varying speed optimization model for the transportation of fresh agricultural products to be processed is proposed considering traffic conditions. An improved genetic algorithm that combines a forward continuous crossover operator and an adaptive differential mutation operator is designed. A Gaussian distribution-based queuing time backward estimation mechanism is integrated, and a binary search algorithm is employed to determine the optimal departure time. Results show that the time-varying speed model with the multi-peak inverse Gaussian distribution can effectively capture the time-varying characteristics of simulated vehicle speed. The proposed mathematical optimization model and algorithm can effectively generate vehicle scheduling plans, thereby contributing to the quality of raw material supply and the improvement of logistics efficiency.

关键词

时变交通 / 车辆调度 / 生鲜待加工农产品 / 改进遗传算法 / 多峰型

Key words

time-varying traffic / vehicle scheduling / fresh agricultural products to be processed / improved genetic algorithm / multi-modal distribution

引用本文

引用格式 ▾
郑加鹏,张立杰,熊宗慧. 考虑时变交通的生鲜待加工农产品运输车辆调度优化[J]. 工业工程, 2026, 29(4): 106-116 DOI:10.3969/j.issn.1007-7375.250113

登录浏览全文

4963

注册一个新账户 忘记密码

参考文献

[1]

王琪, 吴泽昆, 郭琦, . 组织管理视角下市政交通基础设施智慧化运维管理平台构建研究——以深圳湾超级总部基地片区基础设施项目为例[J]. 建筑经济, 2025, 46(2): 42-51.

[2]

Wang Qi, Wu Zekun, Guo Qi. Research on the construction of an intelligent operation and maintenance management platform for municipal traffic infrastructure from the perspective of organizational management: a case study of Shenzhen Bay super headquarters base area infrastructure project[J]. Construction Economy, 2025, 46(2): 42-51.

[3]

头豹研究院. 2023年中国生鲜农产品供应链研究报告[R/OL]. (2023-03-17). https://www.leadleo.com/report/details/6413c9f8c3b18d74b1ceebf2.

[4]

百度地图. 2025年第1季度中国城市交通报告[R/OL]. (2025-06-12). https://huiyan.baidu.com/cms/report/2025Q1jiaotong/index.html.

[5]

Wu D Q, Wu C X. Research on the time-dependent split delivery green vehicle routing problem for fresh agricultural products with multiple time windows[J]. Agriculture, 2022, 12(6): 793.

[6]

Wu D Q, Li J Y, Cui J Y, et al. Research on the time-dependent vehicle routing problem for fresh agricultural products based on customer value[J]. Agriculture, 2023, 13(3): 681.

[7]

Feng Q, Zhao G, Li W J, et al. Distribution path optimization of fresh products in cold storage considering green costs[J]. Buildings, 2023, 13(9): 2325.

[8]

Amorim P, Almada-Lobo B. The impact of food perishability issues in the vehicle routing problem[J]. Computers & Industrial Engineering, 2014, 67: 223-233.

[9]

张佳傲, 樊双蛟, 王雅君, . 基于水产品剩余货架期的冷链配送路径优化研究[J]. 包装工程, 2025, 46(5): 76-82.

[10]

Zhang Jia'ao, Fan Shuangjiao, Wang Yajun, et al. Optimization of cold chain distribution path based on remaining shelf life of aquatic products[J]. Packaging Engineering, 2025, 46(5): 76-82.

[11]

邵举平, 曹倩, 沈敏燕, . 生鲜农产品配送中带时窗的VRP模型与算法[J]. 工业工程与管理, 2015, 20(1): 122-127.

[12]

Shao Juping, Cao Qian, Shen Minyan, et al. Research on multi-objective optimization for fresh agricultural products VRP problem[J]. Industrial Engineering and Management, 2015, 20(1): 122-127.

[13]

吴瑶, 马祖军, 郑斌. 有新鲜度限制的易腐品生产−配送协同调度[J]. 计算机应用, 2018, 38(4): 1181-1188.

[14]

Wu Yao, Ma Zujun, Zheng Bin. Integrated scheduling of production and distribution for perishable products with freshness requirements[J]. Journal of Computer Applications, 2018, 38(4): 1181-1188.

[15]

付朝晖, 刘长石. 生鲜电商配送的开放式时变车辆路径问题研究[J]. 计算机工程与应用, 2021, 57(1): 271-278.

[16]

Fu Zhaohui, Liu Changshi. Research on open time-dependent vehicle routing problem of fresh food E-commerce distribution[J]. Computer Engineering and Applications, 2021, 57(1): 271-278.

[17]

王能民, 梁馨月, 张萌, . 考虑个体客户满意度的多车程生鲜品配送路径优化[J]. 运筹与管理, 2024, 33(4): 14-20.

[18]

Wang Nengmin, Liang Xinyue, Zhang Meng, et al. Vehicle routing problem of multi-trips for perishable product delivery with considering individual customer satisfaction[J]. Operations Research and Management Science, 2024, 33(4): 14-20.

[19]

Zhang G D, Dai L T, Yin X S, et al. Optimization of multipath cold-chain logistics network[J]. Soft Computing, 2023, 27(23): 18041-18059.

[20]

白秦洋, 尹小庆, 林云. 考虑路网中实时交通的冷链物流路径优化[J]. 工业工程与管理, 2021, 26(6): 56-65.

[21]

Bai Qinyang, Yin Xiaoqing, Lin Yun. The optimization of cold chain logistics route considering real-time traffic in road network[J]. Industrial Engineering and Management, 2021, 26(6): 56-65.

[22]

葛显龙, 葛小波, 徐玖平, . 多通路环境下的动态车辆路径问题研究[J]. 工业工程与管理, 2022, 27(2): 104-117.

[23]

Ge Xianlong, Ge Xiaobo, Xu Jiuping, et al. Research on dynamic vehicle routing problem in multi-path environment[J]. Industrial Engineering and Management, 2022, 27(2): 104-117.

[24]

罗亮, 陈慧璇, 吴张, . 交通与天气状况双重作用下生鲜农产品冷链配送的VRPTW[J]. 系统工程, 2022, 40(6): 67-75.

[25]

Luo Liang, Chen Huixuan, Wu Zhang, et al. Vehicle routes planning of cold chain distribution for fresh agricultural product based on the dual functions of the traffic and weather conditions[J]. Systems Engineering, 2022, 40(6): 67-75.

[26]

Bayati A, Khoa Nguyen K, Cheriet M. Multiple-step-ahead traffic prediction in high-speed networks[J]. IEEE Communications Letters, 2018, 22(12): 2447-2450.

[27]

Wang X, Wang P K, Wang B W, et al. Latent Gaussian processes based graph learning for urban traffic prediction[J]. IEEE Transactions on Vehicular Technology, 2024, 73(1): 282-294.

[28]

Storn R, Price K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11(4): 341-359.

[29]

Brest J, Greiner S, Boskovic B, et al. Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems[J]. IEEE Transactions on Evolutionary Computation, 2006, 10(6): 646-657.

[30]

张生财. 智能优化算法及其应用[M]. 北京: 中国铁道出版社, 2020.

基金资助

新疆维吾尔自治区科技重大专项(2022A01008-1)

新疆维吾尔自治区研究生教育计划创新项目(XJ2025G066)

新疆人才发展基金(XJRC-2025-KJ-PY-KJLJ-045)

新疆维吾尔自治区社会科学基金项目(20AZD004)

AI Summary AI Mindmap
PDF (1508KB)

0

访问

0

被引

详细

导航
相关文章

AI思维导图

/