基于人工智能的物流配送调度算法

Q4 Engineering Measurement Sensors Pub Date : 2024-06-06 DOI:10.1016/j.measen.2024.101247
Yue Ji
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引用次数: 0

摘要

为了提高城市物流配送服务质量,最大程度地满足客户需求,提高服务资源利用率,降低物流配送服务成本,作者提出了一种基于人工蜂群的城市物流配送调度算法。物流配送服务执行过程中经常会出现不确定的动态客户需求,导致按照原计划执行配送服务无法实现成本最优,针对这种动态客户需求的问题,作者进行了问题分析,建立了相应的数学模型,并转化为静态问题进行重新调度。结果表明利用调度算法求解实例 100 次,当车辆 1 和车辆 3 能够满足自身负载时,可以为有新需求的客户提供服务,使配送成本最低。在客户数量较少的情况下,算法可以达到较高的准确性,当客户数量达到一定规模时,算法的稳定性会略有下降。
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Logistics distribution scheduling algorithm based on artificial intelligence

In order to improve the quality of urban logistics distribution services and meet customer needs to the greatest extent, improve the utilization rate of service resources and reduce the cost of logistics and distribution services, the author proposes an urban logistics distribution scheduling algorithm based on artificial bee colony. Uncertain dynamic customer demands often occur during the execution of logistics distribution services, resulting in the inability to achieve optimal cost by executing the distribution service according to the original plan, in response to such problems with dynamic customer needs, the author conducted a problem analysis, the corresponding mathematical model is established and transformed into a static problem for rescheduling. The result shows: Using the scheduling algorithm to solve the example 100 times, when the vehicle 1 and vehicle 3 can meet their own load, they can serve customers with new needs, which can make the delivery cost the lowest. In the case of a small number of customers, the algorithm can achieve high accuracy, and when the number of customers reaches a certain scale, the stability of the algorithm will decrease slightly.

Conclusion

The algorithm achieves the purpose of promptly responding to changes in customer demand and quickly adjusting distribution services.

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来源期刊
Measurement Sensors
Measurement Sensors Engineering-Industrial and Manufacturing Engineering
CiteScore
3.10
自引率
0.00%
发文量
184
审稿时长
56 days
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