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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2023

Autores

Barbosa, M (Autor) Outra; Joao Pedro Pedroso (Autor) FCUP; Viana, A (Autor) Outra

Revista

Título: Computers and Operations Research

Vol. 150

ISSN: 0305-0548

Editora: Elsevier

Indexação

ISI Web of Knowledge - 19 Citações

Scopus - 21 Citações

Classificação Científica

CORDIS: Ciências Físicas > Matemática > Matemática aplicada > Investigação operacional

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11