Towards enhancing the crowdsourcing door-to-door delivery: An effective model in beijing

Abstract

Door-to-door delivery is becoming more prevalent in practice. However, crowdsourcing couriers' uncertainties (delivery distance, monthly income, and the monthly volume of tasks) make it hard for logistics companies to maintain a stable crowdsourcing couriers' participation rate and guarantee a good level of delivery coverage rate. To solve this problem, this paper proposed the crowdsourcing delivery optimization model, which considers the bounded rationality of crowdsourcing couriers, analyses the crowdsourcing couriers' participation rate under three crowdsourcing couriers' uncertainties, and helps logistics companies to decrease the delivery cost by adjusting the delivery price per parcel and delivery distance while guaranteeing a certain level of delivery coverage rate. Further, this paper combined the whale optimization algorithm (WOA) with the model to design a heuristic algorithm for solving the crowdsourcing delivery problem. The experiments were conducted according to a data set from Beijing (China). Experiment results shows that 4.07 million USD a month is enough to provide door-to-door delivery services in 94.22% area of the city, which is feasible for giant companies.