考虑时变交通的生鲜待加工农产品运输车辆调度优化
Optimization of Vehicle Scheduling for Fresh Agricultural Products to be Processed Considering Time-Varying Traffic
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。
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.
| [1] |
王琪, 吴泽昆, 郭琦, |
| [2] |
|
| [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] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
张佳傲, 樊双蛟, 王雅君, |
| [10] |
|
| [11] |
邵举平, 曹倩, 沈敏燕, |
| [12] |
|
| [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] |
|
| [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] |
|
| [17] |
王能民, 梁馨月, 张萌, |
| [18] |
|
| [19] |
|
| [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] |
|
| [22] |
葛显龙, 葛小波, 徐玖平, |
| [23] |
|
| [24] |
罗亮, 陈慧璇, 吴张, |
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [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. |
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)
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