考虑随机需求的最佳无人机机队规模建模

IF 2.1 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

EURO Journal on Transportation and Logistics Pub Date : 2024-01-01 DOI:10.1016/j.ejtl.2024.100127

Yuval Hadas , Miguel A. Figliozzi

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引用次数: 0

摘要

对于时间窗口狭窄的随机配送而言，最后一英里配送尤其具有挑战性。由于电子商务和快递类服务的兴起，以及车队规模和车辆类型对送货成本的影响，这一课题显得非常及时。本研究的一个新贡献是提供了一种优化方法，扩展了新闻供应商模型，在随机需求的情况下，从一个中心仓库出发，根据交付数量和交付重量或有效载荷，提供最佳无人机机队规模解决方案。综合敏感性分析表明，所获得的解决方案是稳健的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Modeling optimal drone fleet size considering stochastic demand

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Modeling optimal drone fleet size considering stochastic demand

The last mile delivery is particularly challenging for stochastic deliveries with narrow time windows. This topic is timely due to the rise of e-commerce and courier type services and the impacts of fleet size and vehicle type on delivery costs. A novel contribution of this research is to provide an optimization approach, extending the newsvendor model, to provide an optimal drone fleet sizing solution with stochastic demand in terms of number of deliveries and deliveries weight or payload from one central depot. The solutions obtained are robust, as shown in a comprehensive sensitivity analysis.

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来源期刊

EURO Journal on Transportation and Logistics Multiple-

CiteScore

4.60

自引率

0.00%

发文量

审稿时长

129 days

期刊介绍： The EURO Journal on Transportation and Logistics promotes the use of mathematics in general, and operations research in particular, in the context of transportation and logistics. It is a forum for the presentation of original mathematical models, methodologies and computational results, focussing on advanced applications in transportation and logistics. The journal publishes two types of document: (i) research articles and (ii) tutorials. A research article presents original methodological contributions to the field (e.g. new mathematical models, new algorithms, new simulation techniques). A tutorial provides an introduction to an advanced topic, designed to ease the use of the relevant methodology by researchers and practitioners.