A data-driven compensation scheme for last-mile delivery with crowdsourcing

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Barbosa, M (Author) Other; Joao Pedro Pedroso (Author) FCUP; Viana, A (Author) Other

Journal

Title: Computers and Operations Research

Vol. 150

ISSN: 0305-0548

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 19 Citations

Scopus - 21 Citations

Scientific classification

CORDIS: Physical sciences > Mathematics > Applied mathematics > Operations research

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-00X-CRJ

DOI: 10.1016/j.cor.2022.106059

Abstract (EN): A recent relevant innovation in last-mile delivery is to consider the possibility of goods being delivered by couriers appointed through crowdsourcing. In this paper we focus on the setting of in-store customers delivering goods, ordered by online customers, on their way home. We assume that not all the proposed delivery tasks will necessarily be accepted, and use logistic regression to model the crowd agents' willingness to undertake a delivery. This model is then used to build a novel compensation scheme that determines reward values, based on the current plan for the professional fleet's routes and on the couriers' probabilities of acceptance, by employing a direct search algorithm that seeks to minimise the expected cost.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11