Dynamic Workforce Scheduling and Relocation in Hyperconnected Parcel Logistic Hubs
arxiv(2024)
摘要
With the development of e-commerce during the Covid-19 pandemic, one of the
major challenges for many parcel logistics companies is to design reliable and
flexible scheduling algorithms to meet uncertainties of parcel arrivals as well
as manpower supplies in logistic hubs, especially for those depending on
workforce greatly. Currently, most labor scheduling is periodic and limited to
single facility, thus the number of required workers in each hub is constrained
to meet the peak demand with high variance. We approach this challenge,
recognizing that not only workforce schedules but also working locations could
be dynamically optimized by developing a dynamic workforce scheduling and
relocation system, fed from updated data with sensors and dynamically updated
hub arrival demand predictions. In this paper, we propose novel reactive
scheduling heuristics to dynamically match predicted arrivals with shifts at
hyperconnected parcel logistics hubs. Dynamic scheduling and allocation
mechanisms are carried out dynamically during delivery periods to
spatiotemporally adjust the available workforce. We also include penalty costs
to keep parcels sorted in time and scheduling adjustments are made in advance
to allow sufficient time for crew planning. To assess the proposed methods, we
conduct comprehensive case studies based on real-world parcel logistic networks
of a logistic company in China. The results show that our proposed approach can
significantly outperform traditional workforce scheduling strategies in hubs
with limited computation time.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要