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出 处:《计算机工程与应用》2015年第2期241-244,共4页Computer Engineering and Applications
基 金:国家社科基金青年项目(No.11CGL105);北京市属高等学校人才强教计划(No.PHR20110877)
摘 要: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。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 Feature 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 example 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.
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