摘要
零担快运分拨中心作为干支线运输的重要协调节点,承担货物的快速集散与高效中转任务,对自动化设备间的联合调度与高效衔接提出更高要求。本文针对零担快运货物“快进快出”的越库作业特点,以最小化最大完工时间为优化目标,构建调度水平搬运AGV(Automated Guided Vehicle)与垂直装卸存取无人叉车的混合整数规划模型;进一步引入灵活充电策略,联合优化作业任务与充电任务;结合问题的分解结构,设计Logic-based Benders分解的精确算法,提升大规模问题的求解效率。通过不同规模算例验证模型与算法,结果表明:所提出的算法在求解效率和解的质量方面均优于Gurobi求解器;同时,AGV与无人叉车的联合调度相较于独立调度,可显著提升越库作业的流畅度与资源协同水平;此外,引入的灵活充电策略能够动态优化充电时机与补电量,相较于完全充电策略,平均减少24.3%的充电时间,并使总作业时间降低7.62%,有效提升了物流枢纽运行效率。
As a critical coordination node in trunk-branch transportation,the less-than-truckload(LTL)express hub is responsible for the rapid collection,distribution,and efficient transshipment of goods.This imposes higher requirements on the joint scheduling and seamless coordination among automated handling equipment.Aiming at the“fast-in,fast-out”cross-docking characteristics of LTL operations,this paper proposes a mixed-integer programming model to minimize the makespan by jointly scheduling automated guided vehicles(AGVs)for horizontal transport and automated forklifts for vertical handling.A flexible charging strategy is further introduced to optimize both task assignment and charging decisions in an integrated manner.Based on the problem's decomposable structure,a logic-based Benders decomposition algorithm is developed to enhance the solution efficiency for large-scale instances.Numerical experiments on instances of varying sizes are conducted to validate the effectiveness of the proposed model and algorithm.The results show that the proposed approach outperforms the Gurobi solver in terms of both computational efficiency and solution quality.Moreover,joint scheduling of AGVs and automated forklifts significantly improves the fluidity and resource coordination of cross-docking operations compared to independent scheduling.The incorporation of the flexible charging strategy enables dynamic optimization of charging timing and energy replenishment,reducing charging time by an average of 24.3%and decreasing the total operation time by 7.62%compared to the full-charging strategy,thereby improving overall system efficiency.
作者
唐炜琳
郎茂祥
陈星瀚
TANG Weilin;LANG Maoxiang;CHEN Xinghan(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Key Laboratory of Transport Industry of Comprehensive Transportation Theory,Beijing Jiaotong University,Beijing 100044,China)
出处
《交通运输系统工程与信息》
北大核心
2025年第6期327-340,共14页
Journal of Transportation Systems Engineering and Information Technology
基金
中央高校基本科研业务费专项资金(2024YJS198)
国家重点研发计划(2021YFB1407003)。
