CAJ | 학술논문

城市配送与车辆管理面临着需求与供应不相匹配、需求的时效性和随机性越来越强、车辆利用率低的实际情况。针对该问题提出了在不考虑城市各路段拥堵的情况下的需求驱动下的城市配送车辆动态调度模型。该模型首先用客户订单分类法和自组织特征映射神经网络（SOFM）对客户订单聚类，聚类后确定各个组别的服务优先级；再采用“分派-节约启发式算法”寻找城市配送车辆动态调度问题的满意解。通过Matlab和Lingo软件对实际算例进行数值分析，验证了“需求驱动下的城市配送车辆动态调度模型”对于降低运作成本、缩短运作时间以及减少延期到货等方面具有一定的作用。
성시배송여차량관리면림착수구여공응불상필배、수구적시효성화수궤성월래월강、차량이용솔저적실제정황。침대해문제제출료재불고필성시각로단옹도적정황하적수구구동하적성시배송차량동태조도모형。해모형수선용객호정단분류법화자조직특정영사신경망락（SOFM）대객호정단취류，취류후학정각개조별적복무우선급；재채용“분파-절약계발식산법”심조성시배송차량동태조도문제적만의해。통과Matlab화Lingo연건대실제산례진행수치분석，험증료“수구구동하적성시배송차량동태조도모형”대우강저운작성본、축단운작시간이급감소연기도화등방면구유일정적작용。
City distribution and the management of vehicles face many actual situations, the improperly match of demand and supply, more and more strong timeliness and randomness of the demand, the low utilization rate of vehicle. Without considering all urban road congestion, this paper presents the method of“the demand-driven dynamic configuration of vehicles on city distribution”. The method clusters customer orders according to customer order and Self-Organizing Fea-ture Map neural network(SOFM)to determine the priority of service in every category. It adopts the“assignment-saving heuristic algorithm”to get the satisfactory answer of dynamic configuration of vehicles of city distribution. An actual exam-ple is analyzed through Matlab and Lingo, and the outcome demonstrates that the proposed“the demand-driven dynamic configuration of vehicles on city distribution”can reduce operating costs, shorten the operation time and increase the rate of the arrival of the goods.