考虑客户需求变动的物流配送干扰管理研究

doi:10.3778/j.issn.1002-8331.2304-0211

摘要/Abstract

摘要： 为满足物流配送中的客户多样性需求，解决客户需求变动导致的初始配送计划丧失最优性甚至无法实施的难题，基于干扰管理理论提出物流配送路径实时优化策略。结合物流配送企业、客户和配送人员三方主体在配送活动中的不同需求，建立干扰对各主体的扰动度量函数，并以其加权函数最小化为目标构建物流配送路径干扰恢复模型。设计改进遗传算法对模型求解，考虑配送车辆的混载特性，提出基于双层基因表达的种群个体编码方式及两阶段交叉和变异操作。选取Solomon标准测试算例进行物流配送仿真实验，结果表明该策略对求解客户需求变动下的物流配送路径问题具有可行性和优越性。研究成果能够为物流配送路径的决策制定提供理论支持和实践指导依据。

关键词: 物流配送, 车辆路径优化, 干扰管理, 车辆混载, 改进遗传算法

Abstract: Dynamic customer demands may sometimes make the logistics distribution plan non-optimal or even infeasible. To satisfy customers’ diverse demands and cope with the disruption caused by changes in customer demand, a disruption management strategy is proposed to optimize the distribution vehicle routing problem. The deviation measurements on companies, customers and distributors are first defined. Then a mathematical model that minimizes the weighted sum of deviation measurements is constructed. Next, an improved genetic algorithm is developed to efficiently solve the model. Considering the mixed load attributes of vehicles, two-stage crossover and mutation operation based on individual double-layer gene expression are proposed. Finally, experiments are conducted on instances extended from the Solomon benchmarks. The results show that the strategy is feasible and superior in solving the distribution routing problem with customer demand uncertainty. This research can provide theoretical basis and practical guidance for the route decision in distribution service.

Key words: logistics distribution, vehicle routing optimization, disruption management, mixed-load vehicle, improved genetic algorithm

杨劼, 李婷, 马庆庆, 王璐. 考虑客户需求变动的物流配送干扰管理研究[J]. 计算机工程与应用, 2024, 60(13): 345-352.

YANG Jie, LI Ting, MA Qingqing, WANG Lu. Disruption Management for Logistics Distribution with Uncertain Customer Demand[J]. Computer Engineering and Applications, 2024, 60(13): 345-352.

参考文献

[1] 韩世莲. 基于客户动态需求属性的物流配送线路聚类优化[J]. 系统管理学报, 2016, 25(6): 1146-1153.
HAN S L. Distribution routes clustering and optimization based on customer dynamical demand attributes[J]. Journal of Systems & Management, 2016, 25(6): 1146-1153.
[2] 曹炳汝, 王霞. 基于动态需求的多车型车辆配送路径优化研究[J]. 制造业自动化, 2021, 43(6): 79-87.
CAO B R, WANG X. Research on optimization of distribution path of multi-vehicle vehicles based on dynamic demand[J]. Manufacturing Automation, 2021, 43(6): 79-87.
[3] 刘艳秋, 杨沙. 考虑动态需求的冷链物流配送路径优化[J]. 湖北民族大学学报 (自然科学版), 2022, 40(2): 208-214.
LIU Y Q, YANG S. Optimization of cold chain logistics distribution path considering dynamic demand[J]. Journal of Hubei Minzu University (Natural Science Edition), 2022, 40(2): 208-214.
[4] 王祺, 肖青. 模糊需求下的多中心冷链配送车辆路径问题[J]. 计算机工程与应用, 2023, 59(23): 341-350.
WANG Q, XIAO Q. Multi-depot cold chain distribution vehicle route problem under fuzzy demand[J]. Computer Engineering and Applications , 2023, 59(23): 341-350.
[5] YU G, QI X T. Disruption management: framework, models and applications[M]. Singapore: World Scientific Publishing Co Pte Ltd, 2004.
[6] ZEIMPEKIS V, MINIS I, GIAGLIS G M, et al. Real-time fleet management and rerouting in city logistics[J]. International Journal of Operations Research and Information Systems, 2013, 4(4): 1-21.
[7] 蒋丽, 丁斌, 臧晓宁. 基于干扰管理的车辆故障救援模型[J]. 系统工程, 2010, 28(6): 115-120.
JIANG L, DING B, ZANG X N. The model of vehicle breakdown rescue based on disruption management[J]. Systems Engineering, 2010, 28(6): 115-120.
[8] 丁秋雷, 姜洋, 王文娟, 等. 鲜活农产品冷链物流配送的干扰管理模型研究[J]. 系统工程理论与实践, 2017(9): 2320-2330.
DING Q L, JIANG Y, WANG W J, et al. Disruption management model for cold chain delivery of fresh agricultural products[J]. Systems Engineering-Theory & Practice, 2017(9): 2320-2330.
[9] 宁涛, 王旭坪, 胡祥培. 行驶受扰延迟下配送车辆调度的干扰管理决策模型[J]. 系统工程理论与实践, 2019, 39(5): 1236-1245.
NING T, WANG X P, HU X P. Disruption management decision model for vehicle scheduling under traffic disruption delay[J]. Systems Engineering-Theory & Practice, 2019, 39(5): 1236-1245.
[10] MU Q, EGLESE R W. Disrupted capacitated vehicle routing problem with order release delay[J]. Annals of Operations Research, 2013, 207(1): 201-216.
[11] 辜羽洁, 占维, 魏强. 客户动态变更配送需求的配送路线优化研究[J]. 数学的实践与认识, 2019, 49(19): 28-41.
GU Y J, ZHAN W, WEI Q. Research on route optimization of logistic distribution based on customers’ changing distribution demand dynamically[J]. Mathematics in Practice and Theory, 2019, 49(19): 28-41.
[12] 饶卫振, 金淳, 刘锋, 等. 一类动态车辆路径问题模型和两阶段算法[J]. 交通运输系统工程与信息, 2015(1): 159-166.
RAO W Z, JIN C, LIU F, et al. Model and two-stage algorithm on dynamic vehicle routing problem[J]. Journal of Transportation Systems Engineering and Information Technology, 2015(1): 159-166.
[13] ZHANG H, GE H, YANG J, et al. Review of vehicle routing problems: models, classification and solving algorithms[J]. Archives of Computational Methods in Engineering, 2022, 29(1): 195-221.
[14] KONSTANTAKOPOULOS G D, GAYIALIS S P, KECHAGIAS E P. Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification[J]. Operational Research, 2022, 22(3): 2033-2062.
[15] ABDALLAH A M F M, ESSAM D L, SARKER R A. On solving periodic re-optimization dynamic vehicle routing problems[J]. Applied Soft Computing, 2017, 55: 1-12.
[16] XIANG X, QIU J, XIAO J, et al. Demand coverage diversity based ant colony optimization for dynamic vehicle routing problems[J]. Engineering Applications of Artificial Intelligence, 2020, 91: 103582.
[17] DUTTA J, BARMA P S, MUKHERJEE A, et al. A hybrid multi-objective evolutionary algorithm for open vehicle routing problem through cluster primary-route secondary approach[J]. International Journal of Management Science and Engineering Management, 2022, 17(2): 132-146.