Most current crowdsourced logistics aim to minimize systems cost and maximize delivery capacity, but the efforts of crowdsourcers such as drivers are almost ignored. In the delivery process, drivers usually need to take long-distance detours in hitchhiking rides based package deliveries.
In a new paper by Cheng et al. (2022), researchers propose an approach that integrates offline trajectory data mining and online route-and-schedule optimization in the hitchhiking ride scenario to find optimal delivery routes for packages and drivers. Specifically, they propose a two-phase framework for delivery route planning and scheduling. The historical trajectory data are mined offline to build the package transport network in the first phase. The second phase models the delivery route planning and package-taxi matching as an integer linear programming problem and solves it with the Gurobi optimizer. After that, taxis are scheduled to deliver packages with optimal delivery paths via a newly designed scheduling strategy.
The researchers evaluate their approach with the real world datasets; the results show that the proposed method can complete citywide package deliveries with a high success rate and low extra efforts of taxi drivers.
The study has several important managerial implications for crowd shipping practice regarding extra efforts for crowdsourcers. First, from crowdsourcers’ (i.e., the drivers’) point of view, fewer efforts mean lower cost, increasing the profit margins and the enthusiasm of crowdsourcers for participation in package deliveries.
The efforts of crowdsourcers are a significant factor that affects the quality of the crowdsourcing delivery service. For crowd-based logistic companies, the proposed approach can help to utilize occasional vehicles better to deliver packages and to improve the success rate of deliveries since it is a beneficial tool for package delivery path planning and dynamic delivery scheduling with minimized efforts taken from drivers. Companies can also use the proposed approach to attract more drivers to their platforms, as it could optimally reduce drivers’ detours.
Regarding environmental impacts, the study shows that well-designed routing strategies may scientifically reduce extra travel distance via reducing detours. This will make crowd shipping practice more eco-friendly as it could further mitigate the problems of congestion or pollution in the city.