@inproceedings{cff2db17809c4dd28ed1a89424454ca1,
title = "Workforce planning for last mile delivery: incorporating multi-period dynamics and postponed deliveries",
abstract = "Adopting mixed workforce of in-house and ad-hoc drivers is prevalent in last mile delivery. This paper studies a tactical-level workforce planning problem to determine, in the planning phase, the number of in-house drivers to hire, who will delivery goods together with ad-hoc drivers in the subsequent operational phase. Particularly, we consider multi-period deliveries and allow for postponed deliveries. The objective is to minimize the sum of fixed costs of in-house drivers, variable costs of in-house and ad-hoc drivers, and the penalty costs for postponed deliveries. We develop an integer optimization model and an easy-to-use method to apply the model in data-driven setting. Utilizing data from an online-to-offline retailer in Chongqing as a case study, we conduct numerical tests and sensitivity analysis to evaluate the model's performance, demonstrating its efficacy in reducing costs and improving service level.",
keywords = "Ad-hoc driver, In-house driver, Integer optimization, Last mile delivery, Workforce planning",
author = "Jing Zhang and Yu Zhang and Roberto Baldacci and Jiafu Tang",
note = "Publisher Copyright: {\textcopyright} 2024 SPIE.; 8th International Conference on Traffic Engineering and Transportation System, ICTETS 2024 ; Conference date: 20-09-2024 Through 22-09-2024",
year = "2024",
month = dec,
day = "20",
doi = "10.1117/12.3054580",
language = "English",
isbn = "978-1-5106-8628-1",
volume = "13421",
series = "Proceedings Of Spie",
publisher = "SPIE",
editor = "X Xiao and J Yao",
booktitle = "Eighth International Conference On Traffic Engineering And Transportation System, Ictets 2024, Pt 1",
address = "United States",
}