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

被引：24

作者：

Barbosa, Miguel ^{[1
]}

Pedroso, Joao Pedro ^{[1
,2
]}

Viana, Ana ^{[3
,4
]}

机构：

[1] Univ Porto, Fac Ciencias, Rua Campo Alegre, P-4169007 Porto, Portugal

[2] Ctr Matemat Univ Porto, Rua Campo Alegre 687, P-4169007 Porto, Portugal

[3] Inst Super Engn Porto, Rua Dr Antonio Bernardino Almeida 431, P-4200072 Porto, Portugal

[4] INESC TEC, Campus FEUP,Rua Dr Roberto Frias 378, P-4200465 Porto, Portugal

来源：

COMPUTERS & OPERATIONS RESEARCH | 2023年 / 150卷

关键词：

Last-mile delivery; Crowdsourcing; Social engagement; Dynamic compensation; Probabilistic acceptance; Logistic regression model; SERVICE;

D O I：

10.1016/j.cor.2022.106059

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页数：11

共 26 条

[1] Crowdsourced delivery: A review of platforms and academic literature [J].