Last Mile Delivery with Drones and Sharing Economy

TL;DR

This paper proposes a combined truck and crowdsourced drone delivery system leveraging sharing economy platforms, with optimization models and heuristics to improve last-mile delivery efficiency and practical implementation insights.

Contribution

It introduces new optimization models and heuristics for integrated truck and drone last-mile delivery, incorporating sharing economy dynamics and providing managerial insights.

Findings

Heuristic algorithms effectively solve the NP-hard delivery problem.

Sensitivity analysis reveals key parameters influencing system performance.

The proposed model enhances delivery efficiency and cost-effectiveness.

Abstract

We consider a combined system of regular delivery trucks and crowdsourced drones, available via a sharing economy platform, to provide a technology-assisted crowd-based last-mile delivery experience. We develop analytical models and methods for a system in which package delivery is performed by a big truck carrying many packages to a neighborhood or a town in a metropolitan area and then the packages are assigned to crowdsourced drone operators to deliver them to their final destinations. We develop several optimization models for various cases of the problem and use a combination of heuristic algorithms to solve this NP-hard problem. Finally, we present computational results for the models and algorithms, and conduct an exhaustive sensitivity analysis to check the influence of different parameters and assumptions on the final results. We also provide extensive managerial insights on the benefits of our proposed model if implemented in practice.