Affiliation:
1. College of Information Science and Technology Dalian Maritime University Dalian China
2. College of Electronic Information and Automation Civil Aviation University of China Tianjin China
Abstract
AbstractCrowdsourced package delivery (CPD) has gained great interest from the logistics industry and academe due to its signficant economic and environmental impact. A number of progresses have been reported; however, dynamic pricing, as a special and significant part of the uncertain CPD markets, is far less explored. To address the problem, a novel Delaunay Triangulation (DT) based pricing strategy is proposed for dealing with the imbalanced demand and supply in local markets with the aim to maximizing the profit of the CPD platform. To cater to drivers’ wishes further, the hyperbolic temporal discounting function is applied to estimate their psychological rewards in order to increase the possibility of package acceptance. A three‐stage framework consisting of the DT‐based pricing, the matching pruning and the package assigning algorithm is proposed, to figure out the best‐possible package‐driver matching. With the dataset generated by Brinkhoff road network generator in the city of Jinan and Luoyang, China, a series of experiments is conducted to evaluate the proposed approach against several representative baseline approaches. Experimental results show that the approach significantly outperforms the other approaches in terms of effectiveness and efficiency.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
Institution of Engineering and Technology (IET)